Abstract:In the field environment, picking robots are faced with the problems of a large number of picking tasks, randomness and uncertainty in the positions of targets and obstacles, and so on. Traditional picking path planning methods usually use kinematics equations combined with the shortest path algorithm to solve them, while takes a lot of time to calculate in each planning. In order to improve the efficiency of trajectory planning to adapt to the field picking environment, a virtual robot picking path planning method based on deep reinforcement learning was proposed. Firstly, the virtual robot random action strategies were set according to the real robot physical structure, and the environment observation set was rationally set as the input of the network by analyzing the actual picking behavior. Establishing reward function with the reference to the idea of target attraction and obstacle rejection in artificial potential field method, which was used to evaluate the behavior of virtual robots and improve the success rate of obstacle avoidance. Aiming at the problem that the range repulsion of the artificial potential field method affected the shortest path planning, a directional penalty obstacle avoidance function setting method was proposed, which converted the obstacle range penalty into a single direction penalty. Besides, by establishing a virtual robot motion collision model, the direction penalties were giving selectively by analysis results of the model. Finally, a simulation environment in Unity was built, and the distributed proximal policy optimization algorithm was used to train the virtual robot. The simulation experiment results showed that the success rate of the virtual robot in completing the picking task was over 96.7% under the condition of obstacles in different positions. In 200 random picking experiments, the directional penalty obstacle avoidance function method had a picking success rate of 97.5%, which was 11 percentage points higher than the ordinary reward function method, and the picking trajectory planning took an average of 0.64s/time, which was 0.45s/time shorter than the artificial potential field method. The research results showed that the system can efficiently guide virtual robots to quickly reach random picking points under the premise of avoiding obstacles, and met the requirements of picking tasks, which provided theoretical and technical support for real robot picking path planning.

Abstract:In the actual environment, due to the influence of uncertain factors such as the amount of agricultural machinery operation and the change of soil conditions, the driving condition of following agricultural machinery is unstable, and the response of following cooperative operation is slow, which lead to the difficulty of control. Therefore, in consideration of uncertainty and response performance, a kind of hierarchical control architecture for agriculture machinery was put forward, by building longitudinal dynamic model of agricultural machinery under the field to follow. Furthermore, taking the performance of following distance, following speed, fuel economy, following acceleration as the optimization target, the upper controller based on model predictive control (MPC) algorithm was derived to restrain uncertainty and interference noise. At the same time, to track torque (current) to improve the follow response ability of agricultural machinery, the lower layer controller based on the feedforward and feedback PI controller was designed which took the output of the upper controlleracceleration as the target. The simulation and experiment showed that this control method can effectively solve the following control problem of farm machinery operation. Compared with the sliding mode variable structure controller (SMC), this method can realize stable following driving with smaller speed error and smaller acceleration error. Speed error was controlled in the range of -0.29132~0.18001m/s and acceleration error was controlled in the range of -0.05678~0.05628m/s2. Moreover, the error of stable follow distance was within ±0.45m. The control effect was proved well according to the above data.

Abstract:Aiming at the existing problems in the field test of the primary 4MB-6 row-controlled shoveling and drawing placement machine for cottonstalks in close planting, such as severe soil hilling in the drag reduction device, cottonstalks accumulation in the rowcontrolled shoveling device, discontinuous operation and poor effectiveness of drawingplacing roller and so on, the primary machine were improved. In order to further improve the performance of machine, the working mechanism of main working parts should be analyzed. Adopting the technique of discharging furrow slice insitu and interval operation and when shoveling depth of the rowcontrolled shoveling device was about 11.5cm, the virtual and actual operation ratio of shoveling at bottom and surface was 1∶2.42 and 1∶0.59 respectively that was a continuous decreasing trend from the ground to the bottom, which was helpful to reduce operating power consumption of the machine. Under extrusion and shearing of shoveling plate and side panel with blade of trapezoid frame, the soil around soilroot composite were damaged by shearing and bending and soilroot composite were also damaged and uplifted insitu in upper soil during the process of shoveling, and the rowcontrolled shoveling device had little disturbance to the rest of the soil. The principle of reverse pushing and drawing was adopted when designing the pushingdrawing roller with tooth type. As the diameter of the main part of the cottonstalks was gradually increased from top to bottom, it was helpful to introduce the cottonstalks into Vshaped cutter and clamp the cottonstalks effectively. In addition, because the cottonstalks that would be pulled up was shoveled and lifted, and working depth of the pushingdrawing roller (0~10mm) was small, which both were helpful to further reduce the power consumption of whole machine. The results of field test showed that the improved machine had stable operation performance compared with the primary one. The rowcontrolled shoveling device could work smoothly and achieve the goal of rowcontrolled shoveling and uplifting insitu cottonstalks. The pushingdrawing roller with tooth type could clamp the cottonstalks effectively and separate the soil from soilroot composite when throwing cottonstalks tangentially, and it could also spread cottonstalks in the field. The pulling rate of the improved machine was 90.87%~91.42%, which could meet the design requirements of shoveling and drawing cottonstalks (the pulling rate should be greater than or equal to 90%). It was a suitable equipment for mechanized harvesting of the cottonstalks in Xinjiang cotton area.

Abstract:In order to improve the seeding performance of the seed metering device with low seeding rate for plug seedling raising of super hybrid rice, a piezoelectric vibration seed supply device was designed, and a new type of guide vibrating plate with uniform, orderly and single row feeding under the condition of small seed supply was proposed. The working principle of the piezoelectric vibration seed supply device was described, the dynamic model of the vibration device was constructed, the motion mechanism of rice seed on the vibrating plate was analyzed, and its main working parameters were determined. Taking amplitude and depth of seed box as experimental factors, the simulation test, regression and response surface analysis were carried out. The mathematical models of amplitude, depth of seed box and feeding rate, coefficient of variation of seed supply rate and single column rate were established. The results showed that amplitude had a significant effect on seed supply rate, and seed box depth had an extremely significant effect on single row rate. Under the productivity of 600~1000 plates/h, the mathematical models of amplitude, box depth and single row rate were established. The optimum depth of seed storage box was 9mm, and the amplitude range was 0.4~0.6mm. The results of vibration seed supply performance and seed metering performance prototype test showed that when the power supply voltage was 120~140V, the seed supply rate was 6.1~13.4seeds/s, the variation coefficient of seed supply rate was 10%~14%, the single row rate was 77.5%~84.6%, and the error between the regression model and the regression model was less than 6%, 9% and 4%, respectively, and the variation coefficient of seed supply rate between columns was less than 4%. The results of prototype test showed that the qualified rate of 1~2seeds/hole of Tianyou 998 and Shuyou 217 was 95.54% and 94.88%, and the missing sowing rate was 2.47% and 2.96% when the productivity was 600 plates/h, which met the design requirements of low sowing rate and precision sowing of super hybrid rice. The research provided reference for the design of factory precision seeder for plug seedling raising.

Abstract:Comparison research was carried out on the performance of self compensation and auxiliary compensation in seed metering device, in order to solve the issue of missseeding in notillage corn planter. The performance indicators of metering device at different disc speeds and seed spacing were obtained through the performance test of horizontal disc seed metering device, and the indicators included seeding qualification index, missseeding index and reseeding index. Based on these, the reseeding performance under self compensation and auxiliary compensation methods for missing seeding could be analyzed. The test result showed that when the seeding speed was from 3km/h to 7km/h and the seed spacing was 15cm, 20cm and 25cm, the qualification index of the metering device was decreased with the increase of the seeding speed, and the smaller the seed spacing was, the lower the qualified rate was at the same speed; the missseeding index was increased with the increase of seeding speed, and the smaller the seed spacing was, the higher the missseeding index was. The analysis of the performance of self compensation for missseeding shows that after detecting missseeding signals at the seeding metering port and carrying out accelerated reseeding, the actual seed spacing LPR was larger than 1.5L, and the reseeding spacing was still missseeding, despite that the missseeding spacing was lowered, where precise missing reseeding function could not be realized. In case the missseeding signal could be detected before the seed left the metering hole, and the acceleration preparation was made in advance, then the missseeding could be realized. Selfcompensation for missed seeding was greatly affected by seeding speed and seeding spacing. When the seeding spacing was 20cm and 25cm and the seeding speed was not more than 5km/h, the qualified rate of reseeding was above 88%. When the seeding spacing was 15cm or the seeding speed was above 5km/h, the qualified rate of reseeding was lower. The performance of variable speed seeding would gradually weaken with the increase of seeding speed. Through the analysis of the performance of the auxiliary compensation device for missseeding, at the seeding speed of 3~7km/h and the grain spacing of 15~25cm, the success rate of reseeding was above 89%, and the qualified rate of reseeding was above 96% at the seeding speed of 5km/h or below. It was concluded that the reseeding position should be ensured to be precise, where the installation position of the compensation device for missseeding should be reasonably designed. In the meantime, after reasonably design of the compensation reseeding device installation indicators, the t (response time) and vb (linear speed of compensation device seeding discs) should be controlled to realize the precise control of the reseeding position, as they may be affected by seeding speed, seeding spacing, seeding disc linear speed and the seeding angle. 

Abstract:Seedmeter is highheight installed by many precision planters. Seeds go through tube and get a high speed before implantation in those planters. Shift caused by a collision in high speed leads to bad uniformity of seed distance. To explore the law of seed implantation distribution based on highheight planting, an absolute arm with threedimensional (3D) laser was used to scan the soil surface profile of seed furrow, a 3D digital model of seed furrow was constructed, contact parameters between seeds and soil were calibrated. Coefficient of rolling friction, coefficient of sliding friction and collision recovery coefficient were 0.22, 0.727 and 0.16, respectively. Compared with the real test results, the distance error between implanted seed and outlet of seed tube by simulation was 4.7%. Operating speed, spacing in the rows and seed throwing angle were taken into account. Longitudinal offset of seed implantation point and the first landing point were taken as the indexes. A single factor test and a 2×4 full factor test were carried out. Singlefactor test results showed that spacing in the row had no significant effect on longitudinal offset (P>0.05), while seed throwing angle and operation speed had significant effect on the longitudinal offset of seeds (P<0.01). Full factor test result indicated that longitudinal offset was increased with the increase of operation speed under same seed throwing angle; longitudinal offset was increased with the increase of seed throwing angle under the condition of same operating speed. There was a linear correlation between longitudinal (along operation direction) velocity and longitudinal offset. Operation speed and seed throwing angle affected seed implantation distribution by influencing the longitudinal velocity between seed and seedbed. Field trials were conducted, results showed that with the increase of longitudinal velocity, the qualified index of spacing in the row first was increased and then decreased, and the coefficient of variation was firstly decreased and then increased, which further verified the conclusion of simulation test.

Abstract:In view of the problems such as easy blockage of opener and poor sowing quality when corn no tillage planter works at high speed in Huang-Huai-Hai region of China, an active anti blocking device with shallow rotating strip was designed based on the anti blocking theory of rotary tillage. According to the situation of wheat seedling belt in wheat and corn planting mode in Huang-Huai-Hai region, the knife layout structure and cutter shaft speed of the anti blocking device were designed; the rationality of the structural parameter design of the anti blocking device was determined by analyzing the straw flow, throwing track and force, and the key factors affecting its performance were tested in soil bin; the discrete element simulation and multi factor orthogonal test were carried out selecting the cutter shaft spacing, cutter shaft speed and forward speed as the influencing factors, taking the straw cleaning rate and soil breaking rate as the performance evaluation indexes, the cutter shaft spacing and working parameters of anti blocking device were optimized. The results of simulation test showed that the comprehensive operation quality was the best when the rotation speed of cutter shaft was 800r/min, the distance between cutter shafts was 70mm, and the forward speed was 7km/h. The field experiment of corn sowing was carried out on the optimized results. Under the operation conditions of straw mulching amount of 1.02kg/m2 and forward speed was 8km/h, the rate of removing straw was 91.85%, the stability of ditch depth was 86.67%, and the rate of excavation was 26.47%, which could meet the requirements of highspeed operation.

Abstract:The disadvantages of artificial grafting are low efficiency and nonstandard quality of grafted seedlings. Therefore, this method cannot meet the needs of mass production of factory seedlings. Mechanical grafting can improve the quality of grafted seedlings and promote the standardization of grafting seedlings. At present, most of the grafting machines adopt the artificial method to carry on the seedling, and the single hand grafting limits the improvement of the production efficiency. Through the development of automatic seedling device to replace artificial seedling, the device has high requirements for seedling standardization, the success rate of seedling is only about 80%, and it cannot be used in actual production. Through the study of multi claw synchronous grafting process flow and reasonable optimization of grafting mechanism layout, grafting efficiency can be improved steadily. In the process of mechanical grafting, the clamping and conveying mechanism is the key part of seedling transportation, which is used to grasp and transport seedlings from the seedling loading station to the cutting and docking station. In view of the existing single gripper clamping and handling mechanism, it needs to rotate back and forth at the seedling loading, cutting and docking positions during operation, which limits the grafting production efficiency of the machine, and there are some problems such as clamping injured seedlings, too long waiting time for operators to load seedlings, and easy to fatigue. A four gripper flexible clamping and conveying mechanism was designed. This mechanism can realize synchronous operation of seedling loading, cutting and docking, and realize flexible clamping and rapid transportation of seedlings. It was helpful to improve the grafting efficiency of the machine. The transfer mechanism can complete one grafting seedling every 90° rotation. At the same time, the flexible gripper based on buffer material and the adjustment method of clamping force were also proposed. The compression mechanical properties of EVA cushion material with different thickness were analyzed, and the clamping force of EVA cushion on different seedlings under the condition of completely closed clamping was obtained. By using ADAMS software, the dynamic simulation model of clamping and conveying mechanism was constructed, and the variation rules of different clamping force and rotation displacement of seedlings were analyzed. It was concluded that when the clamping force was less than 0.4N, the seedlings were free from the bondage of the clamping hand. When the clamping force was greater than 3.5N, the seedling clamping and rotating operation was stable. Based on the experimental results of mechanism performance, taking cucurbita moschata and cucumber as the test objects, the average success rate of the flexible gripper was 98.5%, which was 4.5 percentage points higher than that of the arcshaped gripper, and the injury rate was reduced by 3.5 percentage points. The grafting speed of the mechanism was 1052 plants/h, which was 1.72 times of the production efficiency of the same type of single claw grafting machine. The grafting success rate was 96.67%, which greatly improved the production efficiency of grafting robot and met the needs of industrial grafting seedling production. The results can provide a technical reference for the design and optimization of the clamping and conveying mechanism of the highspeed grafting robot.

Abstract:According to the agronomic requirements of small plant spacing for transplanting of clustered varieties of Guizhou pepper planting suitable for machine harvesting, the ISEKI PVHR2 transplanter was modified. After reducing the minimum plant spacing of the machine from 300mm to 150mm, the trajectory changes before and after plant spacing reduction were analyzed. With the goal of reducing the size of the hole and taking into account of the spatial position relationship between the planting device and the whole machine, the opening and closing time of the duckbill and the posture when entering the soil and receiving the seedlings, etcetera, the rods of the planting device were optimized. The optimized simulation results showed that the size of the hole was reduced from 91.1mm to 66.3mm. The transplanting experiment on the film was carried out according to the optimized size, and the test results showed that the width of the hole was slightly smaller than the theoretical analysis due to the elasticity of the mulch. The optimized planting device had a hole size of about 60mm when the planting distance was 150mm, which met the requirements of use. 

Abstract:A seedling pickup mechanism which was driven by planetary secondorder elliptic gear system was developed. The work principle and structural features of the seedling pickup mechanism were introduced. The kinematics model was established, the kinematics property was analyzed and the kinematics simulation was carried out．Both the trajectory and pose of the seedling pickup claw were all analyzed. According to vegetable transplanting agronomy, the best way of separating the seedlings from plug was discussed. Based on the analysis and the simulation mentioned above，structural parameters of the planetary secondorder elliptic gear system were optimized, such as eccentricity ratio of the elliptic gear, the angle between the first middle gear and the second middle gear, the initial angle of planetary carrier and the initial installation angle of pickup claw in respect to it. The optimized seedlings pickup mechanism could take seedlings out of plug along a linear path and release it with upright posture. Finally, an experiment bench with rotary pickingup mechanism was developed and produced. Experiments were carried out to validate the optimization. The result of experiments showed that, at the working frequency of 80 plants per minute, the average success rate of pickingup seedling was 91.3%. 

Abstract:In order to settle the problems of loose spinach harvesting and large rootcutting resistance, starting from the characteristics of rootsoil composite, the interaction between spinach roots, soil and rootcutting shovel in the harvest process was analyzed to optimize root gathering, reduce soil clogging, reduce shovel cutting resistance, and improve spinach root cutting efficiency. Firstly, a new type of rootcutting shovel with both rootcutting and rootgathering functions was designed. A rootcutting force model was established to calculate and optimize the key parameters of the blade. The blade cutting angle was determined as 60°, and the blade angle was 45°; the biomechanical properties of spinach roots were measured, a discrete element model of spinach roots with flexible body was established, and the bonding parameters of spinach roots were calculated based on the constitutive equation of the particle contact model. The spinach rootsoil composite was established in combination with the soil model and the parameters of that were calibrated. A cutting simulation process of the rootsoil composite with rootcutting shovel was built to clarify the working mechanism of the rootcutting shovel, and the main parameters that affected the performance of rootcutting and rootgathering were determined. The response surface simulation design was used to optimize the parameters of the rootcutting shovel. The optimal design parameters of the rootcutting shovel were determined as follows: blade angle was 76°, blade length ratio was 57%, and shove groove area ratio was 40%. Field spinach harvesting test showed that the rootcutting average rate was 93.8%, and the harvesting average rate was 87.2%. This research can provide theoretical guidance for the development of spinach harvester. 

Abstract:China has superior natural conditions and is suitable for the growth of fruit trees. It is a big fruit producing country. The cultivation area and yield of fruit trees rank first in the world all year round. Fruit industry is not only the third largest agricultural planting industry after grain and vegetable, but also the main industry to increase farmers income. Fertilization of fruit trees is a key link in orchard production. The quality of fertilization directly affects the nutrient absorption of fruit trees. Rational fertilization is an important measure to ensure the high, stable and increasing yield of fruit trees. The main forms of fertilization in orchard include depth application of basefertilizer, top dressing of soil, foliar spraying and trunk coating. Among them, the application amount of basefertilizer accounts for more than 70% of the total amount of fertilization in the whole year, which is the most important stage affecting the yield and quality of fruit trees. Mechanization of basefertilizer application is an important embodiment of mechanization level of orchard production and management. The agronomic requirements and development of orchard basefertilizer mechanization were comprehensively analyzed, and the typical machinery and its technical parameters and characteristics of the basefertilizer fertilization equipment in China and foreign developed countries were emphatically elaborated. Combined with the basic agricultural situation and the actual situation of orchard production in China, the main problems to be solved in the development of orchard basefertilizer application mechanization in China were summarized, and the development trend of orchard basefertilizer application equipment was prospected. It provided a reference for the further development of orchard base fertilizer application equipment in China.

Abstract:In order to solve the problems of serious grain breakage and high unstripping rate in the direct harvest of corn in doublecropping area, a longitudinal axial flexible hammerclaw corn threshing device was designed. The threshing device adopted the longitudinal axial flow threshing drum, and the threshing hammerclaw was installed on the threshing drum. Different types of threshing hammerclaw can be replaced in the front and back sections of threshing, and the threshing hammerclaw can be flexibly connected with the threshing drum to reduce the grain crushing rate and realize the flexible and lowdamage threshing of corn. The threshing concave plate adopted a segmented combination type, which was convenient for the adjustment of the threshing section and the separation section. The concave plate cylindrical steel was designed with a semispherical protrusion to increase the rubbing force and improve the removed rate. The feeding amount and drum rotational speed, threshing hammerclaw type were taken as test factors, the orthogonal experiment under different moisture contents was confirmed, roller speed and the best parameter combination of threshing hammerclaw results showed that under the condition of moisture content of 25.12%, the best parameter combination for the drum rotating speed was 500r/min, feeding amount was 8kg/s, the takeoff section was a flat head threshing hammer, and the flat and strong release sections were round head threshing hammerclaw, the grain crushing rate was 3.73%, unstripping rate was 0.69%. Under the condition of water content of 32.83%, the optimal parameter combination was the drum speed of 450r/min, the feeding amount of 8kg/s, the takeoff section, the flat and strong release sections were all round head threshing hammerclaws, and the grain crushing rate and unstripping rate were 4.36% and 0.70%, respectively. 

Abstract:Aiming at the problems that current domestic corn headers continued to be mechanically adjusted and the adjustment was inconvenient, an automatic control system for corn header height was designed. The automatic control system included a floating compression profiling mechanism, STM32 control unit, display screen, key switch, solenoid valve drive module, etc. Floating compression profiling mechanism was composed of angle sensor, profiling plate, torsion spring, fixed shaft, etc. The profiling plate and angle sensor were designed and selected, and the analysis on working process and force of the profiling plate were carried out. ADAMS software was utilized to obtain the vertical height change of the profiling plate under different torque conditions of the torsion spring, and the torsion spring was designed according to the simulation results to achieve better adhesion to the ground. The automatic adjustment parameter model of the header height was established, and PID control algorithm was used to realize the automatic adjustment of the header height. The simulation model was built in Matlab/Simulink software and the system simulation was performed. After tune calculation optimization, when Kp was 1.2, Ki was 0.68 and Kd was 0.9, PID controller could meet the design requirements of the automatic control system of the header height. In automatic profiling mode, the control system detected the height of the header from the ground through the profiling mechanism, and the header cylinder automatically adjusted the height of the header from the ground after processing by the STM32 control unit. In manual mode, STM32 control unit recognized the key signal and controlled the lifting of the header according to different key signals. After completing the design of the automatic control system for the header height, the control system was installed on the 4YZP4HQ corn harvester, and functional tests were carried out. In the manual mode, the adjustment time was taken as the system response index, and a stopwatch was used to record the time required for the header to move from the start to the specified position, and the results showed that the average response speed during adjustment was 0.42m/s. In automatic profiling mode, the control system automatically adjusted the header height from the ground, the height of the header was measured randomly when the harvester stopped every 20~30m, and the result showed that the error between the actual height of the header and the set height was within 20mm. The average speed of the header in manual mode and the actual height in automatic control mode met the needs of the corn harvester header control. The research result could provide reference for the intelligent research of corn harvester.

Abstract:Aiming at the problems of high damage and low efficiency in corn ear harvesting, based on the original research of vibration picking technology, a new type of ear picking device based on elliptical crosssection was developed. Based on the conditions of vibration picking to realize the effective transmission of vibration waved by clamping the fruit handle with the excitation roller, the determination method of the structural parameters of this type of ear picking roller was determined and an elliptical vibration testbed was established. Through the orthogonal test, the main and secondary factors affecting the ear gnawing rate, threshing rate and stem breaking rate were determined as follows: the ratio of the long and short diameter of the exciting roller, the rotation speed of the snapping roller and the diameter of the base circle of the exciting roller. The better combination was determined, that was, the ratio of the long and short diameter of the exciting roller was 0.7, the diameter of the base circle of the exciting roller was 7.5cm, and the rotation speed of the stripping roller was 1000r/min, the ear gnawing rate was 0.38%, the seed dropping rate was 0.12%, and the stalk breaking rate was 0.49%, which were all lower than the requirements of the national corn harvesting machinery technical standards. The experimental verification was carried out under the optimal combination of parameters. The results showed that the ratio of short length to diameter of exciting roller was 0.7, the diameter of base circle of exciting roller was 7.5cm, the rotation speed of snapping roller was 1000r/min, the rate of ear gnawing was 0.39%, the rate of falling grain was 0.12%, and the rate of stalk breaking was 0.48%. The test results showed that the results were basically consistent with the previous test results. 

Abstract:During harvesting of rapeseed, the falling of siliques and seeds caused by colliding and vibration of the harvester header accounts for about 50% of total harvesting loss (8%~10%). To analyze the impact of vibration of header on the harvesting loss during field operation, an experimental study was conducted on the 4LL-15Y crawler rape combine harvester. Through vibration tests, the key vibration excitation sources were determined, which were the engine (27.53Hz) and the cutter bar (7.93~8.53Hz). Then, the frequency range causing the falling of siliques and seeds was determined using a Default Shaker hydraulic vibration system. The hydraulic shaker generated a frequency sweep from 0Hz to 40Hz on the “Huayouza 62” rapeseed stalks, and maximum falling occurred in the frequency range of 5~10Hz. Singlefactor experiments were conducted between the vibration excitation frequency and the falling of siliques and seeds. Results showed that when the frequency was 7Hz, the stalks had maximum falling of siliques and seeds under both horizontal and vertical fixations. The maximum falling ratio was 3.42% when the stalks were under horizontal fixation. It can be concluded that the reciprocating cutter bar, whose excitation frequency was about 8.0Hz, was the main vibration source causing harvesting losses. The research result can provide some reference for the optimization design of rapeseed and grain combine header cutter. 

Abstract:According to the present situation of the low mechanization of field experiments and the lack of plot equipment in China, in order to adapt to the operating environment in hilly and mountainous areas and meet the harvest requirements of super hybrid rice, the 4LZ-21Z type combine harvester was developed. The integrated design of combine harvester and doublespeed doubleaction threshing and separating unit was introduced. The grain plot combine had the functions of holding and dividing grain stems, cutting grain stems, threshing and cleaning of grain and bagging seeds. Low/high speed threshing drum speed, rotary concave screen speed and threshing gap were used as test factors, and grain loss rate, broken rate and impurity rate were used as performance indexes. The experiment was designed by threefactor fivelevel orthogonal rotation combination. The DesignExpert software was used to optimize multiobjective variables, the mathematical model of each test factor and performance index were established, and the multiobjective parameters were optimized. According to the results of parameter optimization, field test of prototype was carried out. Field experiments showed that the performance of the prototype was stable, and the grain loss rate, broken rate and impurity rate were 1.34%, 0.20% and 0.40%, respectively. With each performance index superior to the test standard, this device solved the contradiction between impurity removal, entrapment and grain breakage loss during the harvest of “Yongyou 15” super hybrid rice effectively. This study was of benefit to improving the efficiency and precision of plant field experiments.

Abstract:It is one of the most important information to obtain accurate grain yield for precision agriculture. In order to further improve the accuracy and stability of grain yield monitor system, a new dynamic selfcalibration method which was based on the first generation of photoelectric grain yield monitor system and the principle of quantitative screw conveying was designed. The system was composed of grain volume sensor, unloading grain cylinder speed sensor, grain tank state sensor, data acquisition and processing module, display terminal and error feedback calibration software. In order to verify the accuracy of the system, the simulation test of quantitative screw conveying which was at different rotation speeds and different inclination angles was carried out. In June 2020, the field performance experiments were carried out at Beijing Xiaotangshan National Precision Agriculture Research and Demonstration Base. The performance test results of the unloading speed sensor showed that the error of the unloading speed sensor was less than 2%. Bench test results showed that the error between the monitored value of the system and the actual output value was less than 2.5% at different unloading speeds. There was a linear correlation between the flow rate and the rotational speed, and the correlation coefficient was 0.9937. The field error dynamic selfcalibration experiment result showed that the relevant error was -2.95%~3.13%, which was decreased by 0.45 percentage points compared with that of the measuring device without this system. At the same time, the error fluctuation of the system was reduced. The dynamic selfcalibration system provided a new method to improve the accuracy of grain yield monitor.

Abstract:In order to improve the design efficiency of the threshing device，an intelligent design platform for the threshing device of a rice and wheat combine harvester was constructed. Firstly, the structural characteristics and design knowledge of key parts of threshing device were analyzed. The methods and technologies of collecting, classifying, sorting and expressing design knowledge were studied. The design knowledge of key parts of threshing device was collected, and the design knowledge of key parts of threshing device was expressed by production and framework knowledge representation. The method and technology of using SQL Server 2012 relational database to store the design knowledge of threshing device were discussed, the design knowledge base was constructed, and Visual Studio 2012 was used as the development tool to realize the functions of knowledge query, addition and deletion by using ADO.NET technology, and the knowledge base management system of combine threshing device was established. Secondly, according to the different structural characteristics of the key parts of threshing device, different parametric modeling methods were studied, Visual Studio 2012 was used as programming software combined with C++ and KF (knowledge fusion) two development languages to secondary development NX software, through extracting the relevant parameters in the design process of threshing device parts, the parametric model library of threshing device was established in NX software. Thirdly, according to the design process of threshing device and the design requirements of parts, the reasoning process of intelligent design of threshing device of rice and wheat combine harvester was studied by using casebased and rulebased forward deductive reasoning method. Based on the analysis of threshing device performance evaluation standards and influence factors, the intelligent design reasoning engine of ricewheat combine threshing device was constructed. Finally, using Visual Studio 2012 as the development platform, combining with SQL Server 2012 database and NX threedimensional software and other tools, integrating knowledge base, reasoning engine, parametric model base and humancomputer interaction interface, the intelligent design platform for threshing device of rice wheat combine was constructed. The intelligent design of threshing device was realized, the utilization rate of design knowledge was improved, the design cycle was shortened, the design cost was reduced, the product quality was improved, and the total agricultural machinery design level in China was improved. 

Abstract:In solving the problem on the mechanized harvest of tumorous stem mustard in the southwest hills area and understanding the tumorous stem mustard biological characteristics and agronomic requirements, a small tumorous stem mustard harvester with flexible gripping function was developed. The structure and working principle of the whole machine were described and analyzed, also the parameters of the core parts of the machine were analyzed and determined theoretically, which got the adjustment clearance of the flexible gripping device was between 60mm and 150mm, the speed of the gripping conveyor belt was 0.37m/s, the maximum gripping force required was 38.04N. The terrain imitation capability and structural dynamic characteristics of the cutting bench were analyzed, the results showed that the allowed topographic relief was 50mm, the maximum amplitude was at the position of the mounting cutter, and the first fifth natural frequency was 115.63~783.60Hz which was much higher than the excitation frequency of the engine and the terrain, so there was no resonance effect. The field test results showed that the cutting and gripping conveying mechanism had stable operation which was with small vibration, powerful cutting and moderate gripping force. The success rate of cutting was 89.5%, the damage rate of tumorous stem mustard was 10.8%, and the actual working efficiency was 0.035hm2/h, which basically met the requirements of the design and agronomic techniques. The research achievement would provide an important reference for the mechanization of mustard industry. 

Abstract:Aiming at the blockage problem in the material conveying of the single longitudinal axial flow wheat combine harvester, the conveying process of the wheat in the screw conveyor, indined conveyor and threshing drum screw feed head was theoretically analyzed, and the main factors affecting the conveying performance of wheat and the optimal parameter range were determined. The EDEM software was used to establish discrete element model of wheat plants during harvest, and the EDEM-Recurdyn coupling method was used to construct a simulation system for the conveying system of wheat from the screw conveyor, through the indined conveyor, to the threshing drum, and wheat migration law, axial velocity and local material mass flow rate changes were analyzed during continuous conveying. Then the feed quantity, screw conveyor speed, indined conveyor drive shaft speed and threshing drum speed were taken as the experiment factors, and the material conveying time was taken as the experiment index, the quadrature orthogonal rotation center combination experiment with four factors and five levels was carried out. The results showed that the influence of various factors on the conveying time from large to small were feed rate, speed of threshing drum, screw conveyor speed, and indined conveyor driving shaft speed. The results showed that when the feed rate was 7.52kg/s, the screw conveyor speed was 308r/min, the indined conveyor driving shaft speed was 369r/min, and the threshing drum speed was 1083r/min, the conveying time was 6.37s, and the conveying time was the shortest. Finally, the highspeed photography technology was used to verify the conveying performance. The results showed that the error between the experiment and the simulation was 4.08%, which verified the reliability of the numerical simulation results and provided a theoretical basis for solving the problem of blockage in the conveying system of the single longitudinal axial flow combine.

Abstract:In view of the difficulty in separation and cleaning caused by the great difference of agronomic morphology and complex physical characteristics of the components of the exfoliates during the mechanized harvesting of Chinese cabbage seeds, a separation and cleaning device composed of an internal flow cylindrical sieve (with a inner spiral auger) and a crossflow suction fan was designed. The structure and working principle of the device were described, and the structure and working parameters of its key components were determined by theoretical analysis.The rotational speed of the cylinder sieve, the inner spiral auger and the crossflow fan were selected as the test factors, the hybrid rate and the loss rate were taken as the performance indexes, the orthogonal test was carried out, and the optimum working parameter combination of the device was obtained by using the comprehensive scoring method and the test was verified.The results showed that the main and second order of the test factors that affected the cleaning performance of the device were speed of the crossflow fan, speed of the cylindrical screen and speed of the auger, and the optimal parameter combination of the separation and cleaning device was speed of the crossflow fan of 70r/min, speed of the auger of 200r/min and speed of the crossflow fan of 700r/min.The performance verification test was carried out under the parameter combination, and the results showed that the impurity content and loss rate of Chinese cabbage seeds were 2.75% and 0.62% respectively, which met the requirements of relevant industry standards. 

Abstract:The regulation, monitoring and display mode of cleaning operation parameters of domestic grain combine harvester air and screen cleaning device is simple and low automation degree, resulting in low cleaning efficiency. Aiming to improve these problems, the theoretical basis of adjusting four cleaning operation parameters (the crank speed of vibrating screen, the opening of air door, the rotation speed of fan and the opening degree of fish scale screen) of the air and screen cleaning device of grain combine harvester were analyzed. The control and monitoring device of each cleaning operation parameter was designed independently. Based on the air and screen cleaning device of combine harvester, the multi parameter adjustable and measurable cleaning system was designed. The automatic control, monitoring and display of the cleaning operation parameters of the existing air and screen cleaning device, and the whole system was driven by electric power, realizing the green operation of the air and screen cleaning device of the harvester. Through the accuracy test, the adjustment accuracy of the four cleaning operation parameters of the multi parameter adjustable and measurable cleaning system was not less than 97.17%, which had good robustness, and can realize the accurate control and realtime display of the four cleaning operation parameters. The model 4LZ-4 full feeding crawler harvester equipped with multi parameter adjustable and measurable cleaning system was used in the field test of soybean harvester with total loss rate and impurity content as evaluation index of cleaning performance. The prototype ran well in the test. The results showed that the average loss rate and impurity content in the field experiment of soybean mechanical harvesting were 3.13% and 2.70%, respectively, which met the requirements of industry standard.

Abstract:In view of the complicated structure and large vibration of the screen combined cleaning device which utilized fan and sieve in the traditional rapeseed combine harvester, the cyclone separation cleaning system with replaceable parts was designed. The system was mainly composed of the blower, the cyclone separator with replaceable parts, pipe, centrifugal fan, etc. Moreover, all parts of the cyclone separator like the upper cone, cylinder part, lower cone, and arc/cone baffle inside were replaceable. Base on the amount of threshing outputs produced by the threshing and separating device of the harvester, the theoretical rotational speed of the blower was calculated, which was not less than 569.6r/min. To meet the minimum air volume requirement for separating the materials other than grain (MOG), it was concluded that the rapeseed outlet diameter of the cyclone separator should be less than 256mm. Based on kinematics and dynamics, the motion equations of a single rapeseed in the steady airflow field inside the cyclone separator were established, and the influence of the baffle on the separation performance of rapeseed was analyzed. Furthermore, the singlefactor experiment was conducted to find out the effects of the rotational speed of the blower, and the air volume of the MOG outlet on the cleaning ratio and loss ratio of the cyclone separation cleaning system. After that, the orthogonal was carried out to find the optimal combination of blower rotational speed, the air volume of the MOG outlet, the angle of the upper cone, the type of baffle, and the rapeseed outlet diameter. The results of the singlefactor experiment indicated that the cleaning performance was better when the rotational speed of the blower and the air volume was in the range of 500~700r/min and 0.566~0.692m3/s, respectively. The results of the orthogonal experiment illustrated that the primary and secondary factors affecting the cleaning performance of the cyclone separation cleaning system were air volume (air velocity) of the MOG outlet, baffle form, angle of the upper cone, rapeseed outlet diameter and rotational speed of the blower. The optimal combination of parameters could be obtained when the air volume of MOG outlet was 0.692m3/s, the rotational speed of the blower was 600r/min, the angle of the upper cone was 30°, no baffle was used, and the rapeseed outlet diameter was 200mm. Under this condition, the cleaning ratio and loss ratio of the cyclone separation cleaning system was 91.50% and 6.02%, respectively. To validate the performance of the cleaning system in actual production, the field experiment was carried out. There was no blockage existing in the blower, the cyclone separator, and the pipe. Finally, the range of the cleaning ratio and loss ratio was 86.80%~94.45% and 5.timization and improvement of the cleaning device for the rapeseed combine harvester.

Abstract:In order to solve the problem of clogging of straw when notillage sowing in Northeast China, a spiralsplit sowing strip cleaning device was designed. The arrangement of the stubble blade and the parameters of the blade curve were determined through theoretical analysis, and the main factors that affected the cleaning effect of the sowing strip were obtained: forward speed of tractor, rotating speed of spiralsplit sowing strip cleaning device and pitch. The simulation model of spiralsplit sowing strip cleaning device was established in EDEM, which was a discrete element software. Quadratic regression general combination experiments were conducted in EDEM by taking the sowing strip straw removing rate as the evaluation index, forward speed, rotating speed and pitch as the test factors. The simulation experiment results were assessed by analysis of variance (ANOVA) and quadratic regression model was set up by response surface methodology with DesignExpert. Analyses showed that forward speed, rotating speed and pitch had extremely significant effect (P<0.01), and rotating speed had a greater influence than other factors. The optimizing function of DesignExpert was used for optimization. The result showed that when forward speed was 2m/s, rotating speed was 400r/min and pitch was 570mm, the sowing strip straw removing rate had optimal result, which was 92.55%. Verification field experiment was carried out to testify the regression models by using the optimal combination of parameters. The experiment value of sowing strip straw removing rate was decreased by 2.89 percentage points compared with predicted value, meeting the requirements of notill seeding. The research result provided a reference for the research on straw cleaning and antiblocking device of notillage seeder in Northeast China.

Abstract:The motion law of castor capsule during shelling process is of great significance to the study of shelling damage. Based on the theory of bonding contact, a simulation model of castor shelling process was established to simulate the movement of castor capsule in the shelling drum. The results showed that in the process of castor shell peeling simulation, when the speed reached 8.50m/s, the capsule of castor just broke after collision with Q235 steel, and the inner seed was not damaged. Therefore, the speed at 8.50m/s was set as the target value. When the rotation speed was 250r/min, the shelling gap was 7mm, and the filling rate was 40%. In the single factor analysis, the influence of drum revolution on the maximum pressure and velocity of particles were significant. With the increase of revolution, the maximum pressure between particles was decreased from 68.78N to 68.10N. The maximum velocity of particles was increased from 8.92m/s to 12.99m/s, and the shelling rate was increased from 91.23% to 91.28%, and then it was decreased to 88.89%. The influence of shelling clearance on the maximum pressure and velocity of particles was followed: with the increase of shelling clearance, the maximum pressure between particles was decreased from 76.93N to 58.69N, the maximum velocity of particles was increased from 12.14m/s to 12.99m/s, and then decreased to 10.05m/s. Furthermore, the shelling rate was firstly decreased from 92.50% to 89.59%, and then increased to 91.41%. In the process of shelling, the average velocity of particles in Xaxis direction was decreased from 4.17m/s to 3.m/s to 7.59m/s;and the average velocity of particles in Zaxis direction was decreased from 6.58m/s to 6.24m/s. In the stage of initial shelling, the particles were concentrated in the middle of the shelling drum, and some castor seeds were accumulated. The castor capsules bounced up after touching the inner drum, fell down and rotated with the inner drum, and then moved toward the outlet. During the stable shelling stage, the castor was concentrated and evenly distributed near the outlet of the shelling drum, and rotated with the inner drum. At the end of the shelling stage, the particles were concentrated at the bottom of the shelling drum, and then moved to the bottom continuously. Most of the castor was discharged from the right side of the shelling chamber. Through simulation, the optimal parameter combination of the shelling process was obtained as follows: rotation speed was 350r/min, shelling clearance was 5mm, and the filling rate was 40%. The test results were as follows: rotation speed was 350r/min, shelling clearance was 5mm, and the filling rate was 30%. Since among the three factors, the rotation speed and shelling clearance were extremely significant factors, and the filling rate was significant factor, the difference was within a reasonable range. The study provided theoretical support for the design of castor shelling machine and its related components. 

Abstract:With the demand of modern agricultural production, corn direct grain harvesting has become the inevitable way to achieve efficient harvest. Cleaning process as an important part of corn direct grain harvesting equipment affects the operation performance of whole machine. Aiming at the problems of high grain loss rate and impurity rate in cleaning mechanism of corn combine harvester, and seasonal influence on traditional test, the method of mathematical modeling, simulation and experiment verification were used to optimize the operation performance and the structure design of cleaning device. Based on cleaning system of CASE 4099 combine harvester, a corn threshing and cleaning test platform was built. The cleaning device mainly included upper sieve, lower sieve, tossing board, tail sieve, crank mechanism, fan, motor and so on. The vibrating sieve selected fish scale sieve and adopted doublelayer asynchronous cleaning operation. The mathematical model of movement process of grain on vibrating sieve was established to obtain the change law of main factors affecting on the cleaning effect, and the change law of the average movement speed and movement distance of grain on vibrating sieve were analyzed considering factors such as inclination angel of vibrating sieve, amplitude of vibrating sieve, rotational speed of crank mechanism driving vibrating sieve, angle between vibrating direction of mixture and sieve surface, angle between wind force of fan and sieve surface. In order to improve the cleaning performance, a vertical adjustable air separated board was designed, mainly including support rod, adjusting rod and regulating handle, the internal flow field velocity distribution could be changed by adjusting inclination angle of air separated board, and optimized the performance of cleaning device. Based on corn threshing and cleaning test platform, the experiment was carried out. The flow field inside cleaning device was divided into three layers by boundary of vibrating sieve surface, each layer selected 20 (4 crosses × 5 columns) wind speed measurement points for data collection. The computational fluid dynamics (CFD) simulation technology was used to determine the optimum inclination angle of air separated board slanted at left or right 18°, in this condition, the wind velocity distribution in flow field was uniform, the wind speed change in vertical direction was the smallest, it was advantageous to cleaning operation. To verify the effect of adjustable air separated board, the test results showed that wind speed at each measurement point was uniform distribution and longitudinal gradient of flow field was small when air separated board slanted at right 18°, which was consistent with simulation results. The orthogonal experiment was carried out with vibrating sieve rotation speed and rotation speed of drive motor of fan as main influencing factors, while grain loss rate and impurity rate as indexes. The results showed that when rotational speed of crank mechanism of vibrating screen was 275r/min and rotation speed of drive motor of fan was 900r/min as the optimal working parameter combination, the loss rate and impurity rate were 1.34% and 1.66%, respectively.

Abstract:Aiming to accurately measure the dynamic weighing system of straw bale in small square baler and reduce the influence of vibration caused by ground jolting and mechanical transmission on the measuring accuracy of straw bale. The influence mechanism of different working speeds of baler and the start or stop of the tractor PTO on the pressure noise signal and angle noise signal of dynamic weighing system of straw bale was analyzed by an experiment. When the sampling frequency of the system was 40Hz, the signal frequency of pressure noise was mainly within the range of 0.1~16Hz. The frequency of the angle noise signal was mainly in the range of 3~4Hz and 16~17Hz. The working speed of baler was positively correlated with the noise signal strength. On the basis of signal analysis, the signal processing method was researched. First of all, aiming to eliminate the influence of singular value about the original signal, the double threshold based on the rule of 3σ method for signal preprocessing was carried out. Then piecewise linear interpolation was used to supplement the vacancy point. Finally, a Butterworth band stop filter was designed to eliminate the noise signal and further improve the filtering precision. The field test results showed that the relative error of straw bale quality prediction was between -4.15% and 4.17% after the signal was processed by the method. The relative error of straw bale quality prediction was between -5.15% and 5.08% after the signal was processed by the method of average filtering. The signal processing method was better than the average filtering. Moreover, this filtering method was more adaptable and met the actual production needs.

Abstract:As one of the important agricultural equipment, the design of harvesting machinery has many typical characteristics, such as complex and diverse structures, strong seasonality, and obvious characteristics of users diversity and customization requirements. The traditional R&D mode have some problems, such as long design cycle, low efficiency and difficult quality assurance. Taking the ear peeling device of corn combine harvester as the research object, according to the relationship among the structural characteristics, technical parameters and performance evaluation indexes of the peeling device, the design method of the ear peeling device based on knowledge was presented. Firstly, the design process of peeling device was clarified, and the modular design scheme was formulated, which was divided into special parts module, general parts module, and standard parts module according to functions. The special module was the core component of the peeling device, mainly including the peeling roller and the pressure feeder; the general module included the feeding roller, the conveying mechanism, the impurity eliminator, the driving mechanism and the fruit spike recovery mechanism and so on; the standard module included the driving part, the connecting fastener and the bearing and so on. Secondly, according to the scope of standards, rules and constraints, the related design knowledge base of peeling device was established, the mathematical relationship between the features, operation form corn varieties, transmission scheme, structure parameters, and operating parameters were analyzed. The representation and storage method of the design knowledge of corn ear peeling device was studied. Meanwhile, the framework representation method was used to decompose the husking plant, and a topdown hierarchical structure was designed. Finally, the computer aided design (CAD) and knowledge engineering were integrated to study the reasoning mechanism design of corn ear peeling device. In addition, the working performance evaluation model of corn ear peeling device was established, including the component life calculation model, the bract stripping rate evaluation model, the grain loss rate evaluation model, and the grain breakage rate evaluation model. Based on the Visual Studio platform, the knowledge base, reasoning machine, evaluation model and humanmachine interface of system were integrated, and a design system of corn ear peeling device with knowledge was developed, which realized the realtime calculation output and parameter evaluation of design parameters under the input of users demand parameters. On the basis of the above research, taking the parameters of TPJ16 corn ear peeling device as an example, the input power at the interface was 7.5kW, the feeding amount was 16.6t, the key structural parameters and motion parameters of the peeling device were calculated and evaluated, and the performance of the design parameters was evaluated. The solution results showed that the peeling rate of bract leaves, grain crushing rate and grain loss rate of the peeling device were 96.01%, 1.42% and 3.25%, respectively. The research results provided a reference for the rapid design of agricultural machinery and equipment.

Abstract:Based on CFD unsteady simulation, the airflow velocity field and droplet deposition model of the fixedpipe cold fogging system in greenhouse were established, and the airflow velocity and droplet deposition characteristics of the fogging system under different operating parameters were analyzed. At the same time, the experimental verification of the droplet deposition characteristics was implemented. Results showed that the fogging system formed vortex flows in greenhouse, which was beneficial to the floating, dispersion and deposition of droplets. The optimal operating parameter of the system was 0.3MPa with air pressure and 0.05MPa with hydraulic pressure. The maximum deposition amount of droplets directly below the nozzle and between the nozzles was distributed in the area of 1m in front of the nozzle spray direction (sampling point 5), decreasing along the nozzle spray direction. The amount of ground droplets deposited directly below the nozzle was lower than that in the middle area, while at the height of 40cm, 60cm and 80cm, the corresponding amount of droplet deposition directly below the nozzle was higher than that in the middle area. The droplets in the area directly below were mainly deposited in the height range of 60~80cm, and the droplets in the middle area were mainly distributed in the height area of 40cm and 80cm. The correlation coefficients of the simulated and measured droplet deposition amount at different heights under different operating parameters were ranged from 0.990 to 0.924. The relative error range between the simulated and measured droplet deposition amount was 0.008~0.374, indicating that the CFD simulation can accurately predict the airflow velocity field and droplet deposition characteristics of the fogging system, and guide its operating parameters optimization. 

Abstract:As an important oil crop in the north of China, the demand for flax had been increasing in recent years. Due to drought and little rain in flax growing area, the yield reduction caused by various diseases, insects and weeds is very serious. However, flax plant protection in arid areas was mainly manual operation or used relatively mature spraying machinery such as wheat and corn. The 3WYP900 type of dryland beard spraying machine was designed for the current dryland beard mechanized spraying operation with low operational efficiency, few supporting models, low degree of automation, mist on the operator injury and other problems, which could realize remote control and skid steering. The key components of the prototype walking steering device, spraying device, spraying rod lifting and folding device were designed and theoretically analyzed and calculated in combination with operational requirements. Different spray nozzle application pressure was set for spraying and spray width test, the test results showed that when the pressure was 0.3MPa, a single spray nozzle coefficient of variation was minimum (coefficient of variation of 0.0096) with the best stability, and the pressure under the most stable spray width (spray width of 9.423~9.622m). In the 0.3MPa pressure occurred under the number of dripping nozzle were less than 3, the maximum volume of a single nozzle was 3 drops, the total number of drops of dripping liquid was 5, antidrip performance was in line with national standards. At the same time, the machine speed steering and braking flexibility, control feedback accurate and rapid, no rollover during the test, stall, spraying interruptions and other phenomena, indicating that the basic machine can meet the design requirements, with the relevant conditions of the field test. The research result could provide reference for the whole mechanization of dryland flax. 

Abstract:In order to ensure the application effect of plant protection, the proper distance between spray boom and plant canopy need to be maintained when field surface relief and soil hardness were changed during the whole working period. Three ultrasonic distance measuring sensors were used to obtain the height information of spray boom, and the sensors data were preprocessed with amplitudelimiting and moving average algorithm. Two dualaxis inclination sensors were used to obtain the posture information of sprayer and spray boom which were installed on the chassis of sprayer and spray boom respectively. And then multisensor fusion algorithm based on weighted average was used to handle the spray boom height information. Then different control strategies were designed for different working states of sprayer by using expert knowledge and experience. According to the established control strategy, the control signal was outputted by the inference engine of expert control to control mechanism which was used to drive the spray boom height adjustment cylinder. The mechanical structure of the boom system was introduced, and the composition and working principle of the boom height intelligent adjustment system (BHIAS) were described. The control algorithm and software realization of BHIAS were elaborated. The work status of external variable spraying system was obtained by CAN bus to achieve synchronization of work status between BHIAS and variable spraying system. The touch screen was used to achieve humancomputer interaction and control parameters was sent to the controller for boom height control, such as amplification coefficient, attenuation coefficient, adjustment tolerance, etc. The BHIAS was applied to 3WZG-3000A boom sprayer which was developed by the research group. Ground tests were conducted separately for testing the adjustment performance of BHIAS. The test results showed that BHIAS can follow the boom height adjustment requirements which was caused by step excitation quickly. When the allowable error of boom height adjustment was 8% and the height of step excitation was 20cm, the maximum adjustment time of BHIAS was no more than 0.75s. 

Abstract:During the field of selfpropelled sprayer, due to the large quality and volume of whole vehicle and its working on the complex and diverse road, which lead to the selfpropelled sprayer prone to slip, and requires an antiskid control strategy to maintain stable driving of the machine. For this reason, a fuzzy antiskid control strategy and controller was proposed. Based on the control system, the simulation analysis of the controlling system was carried out by Matlab/Simulink, the simulation result showed that the fuzzy antiskid control system can effectively control the slip rate at the ideal of 0.05. Finally, the performance of the driving antiskid control system was verified through field tests. The result of the experiment showed that when the design of the fulltime fourwheel drive hydraulically driven sprayer fuzzy antiskid control device was traveling at low speed, the average slip rate was 0.078 with the situation of without antiskid control. By contest, when the opening of the antiskid the average slip rate was 0.028; when the selfpropelled sprayer traveling with a medium speed and the antiskid control was closed, the average slip rate was 0.109. However, when the antiskid control was turned on and the average slip rate was 0.031; when the selfpropelled sprayer traveling with a high speed and the antiskid control was closed, the average slip rate was 0110, but the average slip rate was 0.035 after it was opened. Above experiments indicated that the control system had a good antiskid control effect. The research results provided a theoretical basis for the antiskid control of fourwheel drive hydraulically system of selfpropelled sprayer.

Abstract:In order to reduce the comprehensive cost of orchard spray, it is necessary to evaluate the resource consumption level of application machinery. A typical airassisted sprayer, a singlerotor and a sixrotor plant protection unmanned aerial vehicle (UAV) were applied for spray test. The results showed that the droplet deposition density of three spraying machines in each layer were all more than 25 droplets/cm2. The droplet distribution uniformity decreased in vertical canopies seen from the direction of blowing. Observed from the horizontal direction, the droplet distribution uniformity was also decreased from outside to inside layers. The highest coefficient of variation (CV) values were separately 63.54% and 79.19%. In terms of the droplet penetration, the airassisted sprayer was superior with the low CV value nearby 5.35%. While the CV value of the singlerotor plant protection UAV was 35.20% in the horizontal direction and the CV value of sixrotor plant protection UAV was 40.77% in vertical direction with bad penetration. The droplet loss on the ground of the singlerotor and sixrotor plant protection UAV were 2.78% and 12.50% of that of the airassisted sprayer, respectively, which reduced the pesticide waste. Then, two resource consumption evaluation models of application machinery were constructed using two linear weighting methods (objective weighting method based on coefficient of variation and subjective weighting method) with the evaluation indexes of water, pesticide, labor, time, and energy consumption. The results showed the descending order with resource consumption of the singlerotor plant protection UAV, the sixrotor plant protection UAV and the airassisted sprayer. The CV values of comprehensive evaluation index in two evaluation methods were 110.2% and 74.2%, which indicated that the evaluation model based on the objective weighting method was better. The conclusions provided a reference for farmers to choose a suitable application machinery and reduce the comprehensive cost in orchard. 

Abstract:At present, most domestic airassisted sprayers of orchard adjust air volume by controlling fan speed or air outlet sectional area, not realtime regulation air volume according to characteristics of fruit trees. Orchard spraying has problems of pesticide waste and insufficient spraying. In order to solve above problems, a single fan multi  duct bypassair conditioning technology was proposed. It can realize airvolume adjusted by controlling disc valve opening degree at the air outlet. In order to achieve accurate and rapid regulation of air volume, two kinds of variable air volume technologies of throttling and bypassing were designed and compared. The test results showed that the linear relationship between wind speed and butterfly valve opening of bypassing adjusting air was more obvious, which was more conducive to the control of air volume and wind speed. Bypassing air volume adjust technology was selected. Fanshaped air outlets of corresponding number were set based on number of canopy layers of fruit trees. Butterfly valve opening model based on divided canopy characteristics was analyzed and constructed, and opening of each outlet butterfly valve can be calculated according to this model. It can control butterfly valve opening combined with PID variable control technology and achieve the air volume control of each outlet for variable spray. Three spray mode among conventional air spray mode and automatic target air spray mode and variable air volume variable spray volume spray mode were selected to verify testing. The spray performance test of three operation modes was carried out based on droplet deposition and drift loss of pesticides. Test results showed that drift and ground loss of pesticides were the largest in conventional air spray mode among three spray modes. The amount of deposition on surface of canopy in variable air volume spray mode was increased by 17.3% compared with automatic target air delivery spray mode and the coefficient of variation was reduced by 10.29 percentage points. The amount of ground deposition under the canopy was decreased by 26.1%, and reduced by 40.7% between canopies. And the amount of drift was reduced by 69.9% and 50.9% compared with that of the other two spray modes. 

Abstract:In order to research on the effect of different spraying modes of fan nozzle on spatial deposition of droplet, droplet size measurement test device and deposition distribution test device were established by using NJS-1 wind tunnel for plant protection. The droplet size measurement test device was mainly composed of spray system, laser particle size analyzer and so on. The nozzle was mounted on the vertical reciprocating guide rail with the moving speed of 6.7cm/s and the horizontal distance between the nozzle and the laser beam was 30cm. During the tests, the spray pressure was firstly stabilized, and then the laser particle size analyzer was turned on. In order to sample the entire spray stoke area, the spraying nozzle was controlled by a singlechip microcomputer to move at a certain speed. Droplet deposition distribution test device was mainly composed of spray system, wind tunnel system, acquisition system and so on. During the tests, the flow rate of the spray nozzle was controlled by an electronic timer to open/close the solenoid valve to ensure that the spray time of each test was fixed at 10s. The fluorescent tracer BSF was selected as the spray medium and was mixed with water at the ratio of 0.30g/L. After each spray test, the collection line was placed in the plastic bag with 30mL deionized water for full oscillation washing, the amount of fluorescent agent content was determined by the calibrated fluorescence analyzer for each test eluent. The LURMARK-04F80 standard fan nozzle was used in the dropsize distribution and deposition performance tests. The effects of spray pressure and wind speed on droplet size and the influence of wind speed, spray pressure, spray orientation and nozzle direction on droplet deposition were investigated. Three calculation models were employed to compare different influence factors of droplet drift reduction percentage. The results of droplet size distribution experiments showed that at the same wind speed, the increase of spray pressure would cause the decrease of DV0.1, DV0.5 and DV0.9 and the increase of ΦVol＜100μm, but minor changes of droplet spectrum width S; under the same spray pressure, the increase of wind speed would cause the increase of DV0.1 and DV0.5 but minor change of DV0.9, the decrease of ΦVol＜100μm and droplet spectrum width S was from 1.44 to 1.17. The results of droplet deposition distribution tests showed that when spray pressure was increased from 0.2MPa to 0.4MPa, in the plane parallel to spray direction，the droplet deposition was increased at 2~3m from the spray nozzle，droplet deposition was decreased when spray pressure was increased far away from the nozzle, in the plane vertical to spray direction, the droplet deposition was increased at 0.1~0.2m from the ground and increased when spray pressure was increased, in the middle position, the droplet deposition was decreased when spray pressure was increased, the droplet deposition was close to zero at the height nearest to the nozzle. When wind speed was increased from 1m/s to 5m/s, the droplet deposition was increased on both planes parallel and vertical to spray direction; when the nozzle direction was changed from -15° to 15°, the droplet deposition was increased on both planes parallel and vertical to spray direction; when the nozzle direction was changed from 0° to 30°, the droplet deposition was decreased with the increase of nozzle direction on both planes parallel and vertical to spray direction with minor difference. Compared with the reference spray, the values of DPRP obtained from three calculation models showed that spray pressure, wind speed and spray orientation greatly influenced the droplet drift reduction percentage, especially the crosswind speed. This study can provide experimental data guidance for the selection of spray parameters for spray operation in the field. 

Abstract:The current maintenance strategy for the inservice agricultural machinery equipment is mainly post maintenance, which often results in poor economy, low maintenance efficiency, and the inability to ensure the reliability and safety of agricultural machinery equipment in service. Aiming at these problems, a preventive group maintenance strategy for inservice agricultural machinery equipment was proposed. Firstly, the fuzzy clustering analysis method was used to classify and grade the failure data of agricultural machinery equipment, and the reliability evaluation model of agricultural machinery equipment based on improved competitive Weibull distribution was established, and the reliability level of agricultural machinery equipment was quantitatively evaluated as well. Secondly, based on the seasonal service characteristics and the economic correlation of agricultural machinery equipment, the algorithm model of preventive group maintenance time interval and maintenance opportunity was given. Finally, considering the relationship between the maintenance personnel and the number of agricultural machinery equipment in service, the algorithm model with the minimum maintenance cost as the goal was established, and the group maintenance plan of agricultural machinery equipment was obtained. Combined with the historical failure data and maintenance cost data of 10 small combine harvesters in a farm in Chongqing, the specific implementation case of group maintenance strategy in the service stage of agricultural machinery equipment was given. The results showed that compared with the traditional post maintenance method, the preventive group maintenance strategy reduced the total maintenance times and the total maintenance cost by 22.37% and 19.11%, respectively, which verified the effectiveness of preventive group maintenance strategy in the service stage of agricultural machinery equipment. The proposed method provided an important reference for the research work of maintenance strategy for agricultural machinery equipment. 

Abstract:Weeds is an important factor leading to crop yield reduction, how to identify accurately is the premise and basis of weed management. With the progress of computer and information technology, the combination of machine vision and image processing has become the mainstream method of weed detection and recognition. From the point of view of image preprocessing, segmentation, feature extraction and classification, the current research progress of field weed recognition at home and abroad, as well as the advantages and disadvantages of various segmentation, extraction and recognition methods were introduced in detail. In addition, the effects of light environment, the occlusion and overlap of leaves, and the optimization of classifiers in weed detection in the field were analyzed and discussed. Finally, the suggestions and prospects for the current research trend of weed identification were put forward. 

Abstract:Chinese named entity recognition in agricultural diseases and pests domain(CNER-ADP) plays an important role in agricultural natural language processing such as relation extraction, agricultural knowledge graph construction, and agricultural knowledge question and answering, but it still presents some problems, i.e., the neglect of inherent semantic information and local contextual features and the insufficiency of capturing longdistance dependencies, which will lead to low accuracy and robustness. To solve the above problems and tackle the CNER-ADP task, a novel Chinese named entity recognition method for agricultural diseases and pests via jointly using radicalembedding and selfattention (RS-ADP) was proposed. Firstly, the model integrated radical embedding and character embedding as input to enrich semantic information. Among them, three different strategies, including CNN and BiLSTM were both designed to capture the radicallevel embedding. Secondly, a CNNs layer with different kernel sizes was considered capturing multiscale local contextual features. Thirdly, based on the BiLSTM layer, selfattention mechanism was used to further enhance the ability of the model to extract longerdistance dependencies. Finally, the conditional random field (CRF) was utilized to identify entity boundaries and category. The experiments were carried out on the corpus of agricultural diseases and pests, named AgCNER, which contained 11 categories and 24715 samples. At macrolevel, the RS-ADP model achieved optimal precision, recall, and F1 values of 94.16%, 94.47%, and 94.32%, respectively. In terms of specific categories, it achieved F1 values as high as 95.81%, 97.76%, and 97.23% on easily identifiable entities such as crop, disease, and pest. Meanwhile, this model still maintained over 86% of F1 value on some other difficultly recognized entities such as weed and pathogeny. The experimental results showed that the proposed model could effectively recognize the named entities of agricultural pests and diseases without feature engineering. Moreover, it had certain generalization and outperformed other models. 

Abstract:Aiming at the problem of autonomous intrarow navigation of orchard vehicles, an intrarow path extraction method based on light detection and ranging (LiDAR) was proposed, and a diversified virtual orchard environment to simulate the intrarow path navigation process and evaluate the performance of path extraction algorithm was constructed. A 2D LiDAR was used to measure orchard trunks during the extraction of intrarow path and median filter was used to weaken the measurement noise. Then an elliptical region of interest (ROI) was designed to extract adjacent tree rows, followed by a twostep tree row segmentation method which classified the data into the left and right tree rows. Finally, the tree line was fitted by the least square method and the center line of the tree row was determined as the navigation path. The virtual orchard environment and LiDAR measurement model were established for the simulation of intrarow navigation. The navigation path was generated based on the simulation measurement data and the vehicle movement was controlled in realtime after using a firstorder digital lowpass filter. In the simulation experiments, the planting deviation of fruit tree was set to be ±20cm, the deviation of trunk diameter was ±3cm, and the measurement error of LiDAR was ±3cm. Experimental results showed that the proposed method can extract the navigation path accurately in the case of vehicle yaw, missing tree and curve tree row. When the yaw angle was not more than 15°, the lateral deviation was not more than 1m, and the missing tree rate was not more than 25%, the lateral deviation between vehicle track and path centerline can be controlled within ±14cm. 

Abstract:Citrus is an important fruit and it’s strongly relevant between quality and irrigation. Traditional irrigation strategies relying on human experience caused two problems, i.e. inaccurate irrigation timing and quantity. Both of the two problems have negative influence on citrus. The evapotranspiration of citrus orchard is an important index of water consumption. In order to evaluate citrus orchard evapotranspiration (ET) to make more scientific and precise irrigation strategies, the long shortterm memory (LSTM), extreme learning machine (ELM) and general regression neural network (GRNN) methods were applied to model ET and test its performance based on climatic data. The result showed that LSTM performed the best in mean absolute error (MAE) and root mean square error (RMSE) than the other two models. And ELM model performed closely to GRNN. In order to evaluate the certainty of three models, the Monte Carlo analysis method was added to the process of training. The result indicated that LSTM had good accuracy in different input features while ELM tended to overestimate ET and GRNN tended to underestimate ET. It’s practical to applicate the proposed method to make precise irrigation strategies. 

Abstract:In the process of maize breeding, yield tests and the improvement of maize production and the examination, including the measurement of the length, diameters, row numbers, grain numbers per row and grain numbers of ears, is necessary. However, manual examination utilized for a long time not only needs to spend a lot of manpower and resources, but also has many problems, such as high labor intensity, low efficiency of observation and the nonobjective and inaccurate results caused by human interference, greatly limiting the speed and accuracy of the operation. Therefore, an automatic equipment of examination with the machinevision was presented. The colour images of singleface characters of maize ears were obtained by industrial cameras through USB. Then the model |B-R| and (G+B)/2 were respectively applied to gray the colour images. After that, the method of segmentation of onedimension maximum entropy was used to achieve binaryzation, obtaining binary images of contours and features of ears separately. Moreover, these two kinds of images were corrected automatically by the calculation of angles of ear contours of binary images. Based on the calibration of cameras, the unit pixel corresponding to the actual value could be gained and then the length and diameters of ears could be calculated. In addition, the width of rows of ears could be got by the scanning of points of horizontal black background and correction of scanning curves, according to the extraction of local features of binaryzation images. The number of rows of ears could be obtained by the modified model of numbers of rows. Furthermore, by the extraction of binaryzation images of local features of single line of grains, the number of grains of rows could be obtained, based on the scanning of the points of black background and its modified curve. Finally, the total number of grains of ears could be computed by the numbers of rows and that of grains in single row. The experimental results showed that the average accuracy of measurement of ear length and ear diameter were 98.05% and 97.99%; the correct rate of measurement of row numbers was 95%; the average measurement accuracy of the number of grains per row was 96.29%; and the average accuracy of measurement of grain numbers was 95.67%. Furthermore, Ttest was conducted to compare the difference with the standard value, demonstrating that there was no significant difference and the equipment was of reliability. The average speed of measurement of the whole ear was less than 600ms per ear, and the measurement speed of the test system was within 6s per ear, meeting the requirement of the automatic equipment of examination. This research provided the basis of equipment and technology for the modern seed industry, even for the development of agricultural information technology.

Abstract:Chlorophyll is an important pigment in photosynthesis of plants. It can provide important basis for realtime monitoring and health diagnosis of crops by using crop spectral and texture information to retrieve chlorophyll. In the field environment, five different varieties of corn at four leaves stage and jointing stage were selected as the research objects. The visible light images were obtained by UAV, and the soil background was dealt with mask treatment. Totally 25 kinds of visible light vegetation index and 24 kinds of texture features were extracted. The correlation between vegetation index, texture feature and relative chlorophyll content (SPAD) of corn was comprehensively analyzed, and stepwise regression (SR), partial least squares regression (PLSR) and support vector regression (SVR) models based on vegetation index, texture feature and vegetation index + texture feature were respectively established to quantitatively estimate relative chlorophyll content. In SR model, vegetation index+texture feature model was the same as vegetation index model, which was better than texture feature model, R2 was 0.7316, RMSE was 2.9580, RPD was 1926; in PLSR model, vegetation index+texture feature model was better, texture feature model was the second, vegetation index model was the worst, R2 was 0.8025, RMSE was 2.4952, RPD was 2.284; in SVR model, vegetation index + texture feature model was better, vegetation index model was next, texture feature model was the worst, R2 was 0.8055, RMSE was 2.6408, RPD was 2158. Comprehensive analysis using the PLSRbased vegetation index+texture feature model can achieve rapid and accurate extraction of corn SPAD, providing a new method and experience for chlorophyll inversion, and also providing a reference for UAV remote sensing growth monitoring. 

Abstract:In order to carry out the nondestructive detection of chlorophyll fluorescence parameters of potato leaves, hyperspectral images of 200 regions of interest (RoI) were collected and the average reflectance was extracted. Then qP values of the corresponding areas were measured by the closed chlorophyll fluorescence imaging system of Fluorcam. Sample set partitioning based on joint X-Y distance (SPXY) algorithm was used to divide the samples into calibration set (135 samples) and validation set (65 samples) according to the ratio of 2∶1. Algorithms of synergy interval partial least squares (si-PLS) and random frog (RF) were used to select feature wavelengths, and the partial least squares regression (PLSR) model was established with the selected wavelengths. The results showed that the calibration accuracy of si-PLS-PLSR model was 0.6285, the validation accuracy was 0.6103, and the calibration accuracy of RF-PLSR model was 0.7093, the validation accuracy was 0.6872. The interpretation of potato leaves by RF method was better than that by si-PLS method. Selected wavelengths mainly distributed in the range of 518.72~640.64nm, 650~800nm and 850~1000nm, which reflected that fluorescence emission signal was an important response characteristic of photochemical absorption in potato crops. And it also showed that the photochemical absorption was closely related to chlorophyll content, leaf structure, water content and other attributes. The mapping of qP values distribution in leaves provided an intuitive method for the analysis of photochemical absorption and photosynthesis dynamics of potato leaves. The study provided a way for the evaluation of photosynthetic activity, which could also be applied in monitoring of complex physiological and biochemical dynamic of potato crops.

Abstract:Mercury ion concentration is one of the key parameters affecting water quality environment, and a method for detecting mercury ion based on gold nanoparticle colorimetry was proposed. The gold nanoparticle colloidal suspension modified by bismuth reagent-Ⅱ was used to detect mercury ion. The mercury ion selectively coordinated with bismuth reagent-Ⅱ, which made the gold nanoparticle colloidal suspension anti agglomerate. There was a certain linear relationship between the concentration of mercury ion and the absorbance of the solution, the linear range was 0.05μg/L~1mg/L, and the relative standard deviation was 1.98%~3.52%. Under the experimental conditions, the characteristic wavelengths extracted from successive projection algorithm were pretreated by Savitzky-Golay first derivative. Through linear support vector machine regression model modeling and analysis, the model had good self prediction ability and practical prediction ability. The correlation coefficient of the calibration set was 0.9685, the root mean square error of calibration set was 0.0412mg/L, the correlation coefficient of the validation set was 0.9600, and the root mean square error of validation set was 0.0434mg/L. Therefore, the method based on gold nanoparticle colorimetry can provide effective support for improving the detection efficiency of mercury ion concentration. 

Abstract:The accurate measurement of soil moisture is of great significance to the fields of watersaving irrigation, moisture monitoring, water and fertilizer integration, and the soil nitrogen content will affect the measurement of the moisture sensor. In order to eliminate this effect, a monitoring experiment of different urea on soil samples with different moisture contents was designed, a highsensitivity moisture sensor was used to monitor the output voltage value under the interference of urea, and the moisture content of the soil sample was monitored by weighing method, the capacitance and resistance of the soil sample was monitored by LCR bridge tester. Totally 800 sets of sample data were obtained, of which 75% were used as the training set and 25% were used as the validation set. In order to study the mechanism of the influence of nitrogen content on moisture measurement, three predictive models, including a threeelement cubic polynomial model, a BP neural network model, and a deep learning model, were established based on experimental data, and error analysis was performed on the prediction results. The analysis showed that the highest errors of the three models were 2.86%, 2.07% and 3.82%, and the errors were concentrated in the range of 0 to 2%, accounting for 89%, 98% and 90%, respectively. The following conclusions were obtained: different urea contents had different influences on the predicted value, which was roughly in a periodic oscillation relationship. When the soil moisture content was lower, the interference of urea content on voltage was greater, and the same was true for impedance, but capacitive reactance was only sensitive to soil moisture, but not to changes in urea. Therefore, the interference of urea on soil moisture measurement was mainly caused by interference with soil resistance. The average absolute errors of the threedimensional cubic polynomial, BP neural network, and deep learning models were 0.77%, 0.64% and 0.75%, respectively, and BP neural network model was the most stable, with the most prediction results concentrated in the low error range. No matter how the urea content changed, the BP neural network prediction value curve can always track the actual mass moisture content curve very well. BP neural network model was superior to other network models in terms of prediction accuracy and stability. Therefore, BP neural network moisture prediction model was established as the best antiurea interference model. The interference of nitrogen content on moisture measurement was eliminated by increasing the data dimension and the prediction model was established, and the prediction accuracy was improved. 

Abstract:Generally, there are two methods to detect soil electrical conductivity, which are contact and noncontact. Among them, the development of contact soil conductivity meter is generally based on the principle of current-voltage fourterminal method, using constant current source as excitation source and voltmeter as feedback signal detection equipment. Based on the principle of current voltage four terminal method, the signal generator instead of constant current source was used as excitation source to provide sine signal with larger amplitude and higher stability, and the digital oscilloscope was used to replace voltage source for feedback signal detection, so as to solve the problem of slow frequency of voltage RMS conversion and AD conversion. A soil conductivity detection system based on digital oscilloscope was developed. The field vehicular measurement experiment was divided into two parts: stability detection and fixedpoint measurement. Under the stability test, the detection system can read the relevant data stably. Field fixedpoint measurement experiment combined with soil sample collection and laboratory experiment, the measured value of soil conductivity and the true value of soil conductivity at each fixed point were obtained. Based on the field experiment data as the ordinate and the laboratory measurement as the abscissa, the data scatter diagram was drawn, and R2 was 0.7531. In order to further explore the problem of poor correlation of experimental data, according to the situation of two kinds of measurement contact surface between electrode and soil to be measured caused by tractor traction plow disc shaking in the experiment. After analyzing and eliminating the influence of tractor shaking phenomenon on the data results, the determination coefficient R2 between the measured soil conductivity data and the experimental data can be increased to 0.8552~0.9066, which indicated that the equipment can achieve a high level of measurement accuracy without the influence of external factors such as measurement methods. According to the comparison of experimental data, the results showed that the vehicle mounted soil conductivity meter based on digital oscilloscope can stably measure in farmland, and had good performance and accuracy.

Abstract:An allsolidstate nitrate doped polypyrrole (PPy(NO-3) ionselective electrode (ISE) was prepared with a nanohybrid composite film of gold nanoparticles (AuNPs) and electrochemically reduced graphene oxide (ERGO). Preliminary tests on the ISE based insitu soil nitrate nitrogen (NO-3N) monitoring was conducted in a laboratory 3stage column. Gold nanoparticles (AuNPs) and electrochemical reduced graphene oxide (ERGO) nanocomposite were used to improve the stability, sensitivity, and lifetime of ISE. The electrode life was significantly improved, and the average response slope was 44.02mV/dec within 65 days. The relationship between soil depth, soil texture, soil moisture, and soil nitrate nitrogen content of percolate was analyzed by the insitu realtime monitoring system of soil percolate. The results showed that different soil depth, texture, and moisture had no effect on the detection of nitrate nitrogen concentration in soil exudate. The nitrate nitrogen was significantly affected by the sampling depth, which was raised by 30~60mg/L with a depth increase of 10cm. the influence of water content was not obvious. The soil particle size of 2.5mm was the influence pole. The influence was not obvious when the particle size was smaller than 2.5mm, while the nitrate nitrogen concentration was decreased by 19.5% in soil percolate solutions with particle size larger than 2.5mm. The determination results of nitrate nitrogen in tested percolate samples by ISE and UV-VIS methods were in good agreement. Obvious differences of 5~6 times concentrated nitrate nitrogen concentration were found between the insitu percolate samples and conventional soil extracts. 

Abstract:In order to ascertain the change law of the substrate moisture content at different depths, drying method was used to calibrate multiple EC-5 sensors, and the four sensors were placed at four different depths, i.e., 5cm, 10cm, 15cm and 20cm vertically from the dripper. The changes of the vertical substrate water content under different dripper flow and drip irrigation conditions were measured, and a prediction model of substrate water content at different depths was established. The test results showed that the substrate moisture content of the first layer (5cm away from the dripper) was risen first after the drip irrigation started and quickly reached a higher level. After the drip irrigation stopped, the moisture would quickly diffuse to the deeper substrate layer, and its moisture content can be increased to the root system easy to use level (25.3% and above), the rapid water migration time lasted for about 1h. With the decrease of the initial substrate moisture content, under the same dripper flow and irrigation conditions, the degree of water migration in the vertical direction was deeper. The initial water content of the first layer of the substrate, drip irrigation time, prediction time, predicted layer height difference, and dripper flow were used as input, and genetic algorithm optimized BP neural network algorithm and random forest regression algorithm (RFR) were used to establish different depths of water content of the substrate under drip irrigation rate prediction model. The predicted water content of the substrate after drip irrigation in the experiment compared with the actual measured water content of the substrate at different depths, and the error analysis was performed on the prediction results of different prediction depths. The results showed that the prediction accuracy (R2) of the GA-BP prediction model and the RFR prediction model were 0.8664 and 0.9465, respectively, that was, the prediction model established by the RFR algorithm was more accurate, and the closer the prediction depth was to the first layer, the more accurate the prediction result was.

Abstract:Soil information plays an important role in guiding agricultural production. Soil electrical conductivity reflects soil information such as soil moisture, salinity, clay content and type, it is significant to obtain soil electrical conductivity accurately for realizing agricultural fine production. Among all kinds of soil conductivity measurement methods, the fourterminal method is widely used in practical measurement because of its low cost, high precision, fast measurement speed and simple operation, its performance directly determines the accuracy and measuring range of the measuring instrument. The effect of three constant current sources on the measuring performance of the measuring instrument was compared. It was found that the fourterminal method using Howland constant current source had the best measuring accuracy and the high measuring ability, but the low measuring range was small. The measuring range of low conductivity by using improved Howland constant current source was enlarged and the measuring precision was good. The measuring range of low conductivity by using constant current source based on differential amplifier was the largest, the measuring range of high conductivity was better and the measuring accuracy was good. 

Abstract:Traditional vision detection methods generally have better image segmentation effect when image foreground and background have obvious chromaticity difference. However, for the maize stubble field harvested by combine harvester, there are other backgrounds besides maize stubble row such as maize residues, naked land surface, and their color are very similar. Therefore, traditional image processing methods are not suitable for the segmentation of maize stubble row. In order to achieve precise and rapid segmentation of maize stubble row, a segmentation method for maize stubble row based on hyperspectral imaging technology was put forward. Firstly, the original hyperspectral image of maize stubble row was corrected by black and white correction algorithm. Then, the principal components analysis algorithm (PCA) was used to analyze the hyperspectral image. And the feature wavelengths (1260nm, 1658nm and 2131nm), which could maximum highlight the stubble tip incision and lighten the backgrounds, was selected according to the weight coefficient curve. In addition, the PCA algorithm was widely used in hyperspectral image analysis because of its effective dimension reduction effect and convenience. Secondly, images at three wavelengths were extracted and analyzed by PCA. After that, the PC2 image was convert into binarization image via single threshold method. Thirdly, the median filtering algorithm, morphological open operation, and edge noise removing algorithm were applied to ensure the precision and integrity of the maize stubble row. Totally 50 test images were collected to verify the segmentation effect of the presented method. At the same time, the segmentation precision rate, recall rate, and F1 value were calculated. The results revealed that the method proposed had good segmentation effect, and the segmentation precision rate, recall rate, and F1 value were 91.85%, 90.49%, and 91.16%, respectively. Therefore, the developed method realized good performance in maize stubble row segmentation and can provide great help for detection of navigation line in maize stubble cropland harvested by combine harvester.

Abstract:In order to study the influence of air inlet type on air age and CO2 of pig house, computational fluid dynamics (CFD) technology was used to simulate the wind speed, air age, CO2 and the convective heat transfer of pigs in an experimental pig house. The angle of the air inlet deflector of the original model (scheme A) was 50°, and the inlet height was 1.8m. At the same time, totally six additional inlet conditions were selected to simulate and compare the pig house with the original pig house. Scheme B: the angle of the air inlet deflector was 90°, and the inlet height was 1.8m; scheme C: the air inlet deflector angle was 120°, and the inlet height was 1.8m; scheme D: the air inlet deflector angle was 150°, and the inlet height was 1.8m; scheme E: the air inlet deflector angle was 50°, and the inlet height was 1.6 m; scheme F: the air inlet deflector angle was 50°, and the inlet height was 1.4m; scheme G: the air inlet deflector angle was 50°, and the inlet height was 1.2m. The results showed that the correlation R2 between the simulated and the measured wind speed value was 0.9162, and the average relative error was 26.7%. This model can accurately predict the airflow pattern in the pig house. Through the comparison of the simulation results of different air inlet deflectors, the scheme C and scheme F can significantly reduce the average air age and average CO2 concentration of pigs in the house, and maintain the heat preservation effect of the pig house. Comparing various air intake schemes, it can be found that the CO2 concentration in the animal occupied zone (AOZ) was not only affected by the average air age in the zone around the pigs, but also by the uniformity of the air age distribution throughout the entire pig house.

Abstract:Biomass briquette is one of the most common energy fuels in some countries. It is essential to achieve the highquality biomass briquette, since the quality has a direct influence on the efficiency of utilization. For the purpose to improve biomass pellet quality, a method of ram compression molding machine on the basis of the numerical control pressure device was conducted. The machine adopted a switched reluctance motor which had high starting torque and can stop/start frequent as a power source. It drived the flywheel by belt drive, then converted the rotary motion of flywheel into the up and down reciprocating motion of the plunger through the screw mechanism. The machine also took the property that flywheel can accumulate energy. The die consisted of three parts, with a structure of “straight-cone-straight”. Any part with different size parameters can be replaced, which can suit for different biomass raw materials. Meanwhile, the lower end of the plunger always reciprocated in the die below the lower edge of the discharge port of the screw feeding device. At the moment, due to the discharge port was blocked, the biomass raw material was precompressed by the continuously screwing helical blade, which improved the subsequent molding efficiency. While working, the plunger would accelerate downwards based on the energy accumulated during the upward and the gravitational potential energy of the slider. Then, the biomass raw materials were compacted and squeezed out. Experiments were carried out with typical biomass raw materials, including corn stalks and sawdust. The results indicated that the molding method had a well feasibility. The briquette was 60mm in diameter and different lengths. All the density of the briquettes was 1.2g/cm3 approximately, the drop resistance index was higher than 95%, and the power consumption was 36.51kW·h/t. All indicators met the requirements of the relevant standards. The proposal of the forming machine can provide reference for the development of biomass densification technology.

Abstract:To solve the problem of extracting the answer for a question from massive food safety incident news reports, a question answering (QA) system was proposed. Firstly, a deep learning method TextCNN was used to classify the question provided by users. Secondly, a search engine method Lucene was used to find the best matching report for the question. Thirdly, based on a food safety event database (a structured knowledge base which was automatically constructed by using the information extraction technology) and the type of the input question, a set of answer sentence candidates was selected from the best matching report. Finally, based on the deep learning model of bidirectional long shortterm memory (BiLSTM) and a feature extraction method which can extract effective information from the contexts of the answer candidate sentences, an answer extraction model was constructed, which can automatically extract the final answer from the given set of answer candidate sentences. To evaluate the impact of the selection method of answer candidate sentences based on the food safety event database and the feature extraction method based on the contexts of answer candidate sentences, different experiments were conducted. The results showed that the QA system using the structured knowledge database and the contextbased feature extraction achieved the best performance (44% in accuracy), which significantly outperformed over traditional QA systems.

Abstract:Precooked meat products generated warmedover flavor (WOF) after cooling and reheating, affecting the meat products’ sensory quality and consumers’ acceptance. It was especially necessary to find natural WOF inhibitors, due to the extensive attention for the safety of chemically synthesized antioxidants. The effect of four natural spicy essential oils at 003% level on the flavor compound profiles, WOF and lipid oxidation of precooked pork patties after cooling and reheating was investigated. These natural spicy essential oils included cinnamon essential oil, clove essential oil, nutmeg essential oil and pepper essential oil. Totally 57 flavor compounds were identified in all samples by solid phase microextraction-gas chromatography-mass spectrometry. The addition of natural spices essential oils increased the types and contents of volatile compounds for reheated samples, mainly including alkens, terpene alcohols and esters （p＜0.05). Hexanal, heptanal, octanal, nonanal, (E)2octenal, (E)2decenal, (E,E)2,4decadienal, 1octene3ol, and 2pentyl furan were selected as the evaluation indicators of WOF. Four kinds of natural spice essential oils had antioxidant effects on precooked pork patties after cooling and reheating, but cinnamon essential oil, nutmeg essential oil and pepper essential oil had no significant inhibition on WOF （p＞0.05). Clove essential oil showed better inhibition on WOF and lipid oxidation than the synthetic antioxidant, dibutyl hydroxytoluene for precooked pork patties after cooling and reheating. This study revealed the clove essential oil as a potential natural inhibitor to WOF in precooked meat products after cooling and reheating. 

Abstract:The air flow laser fusion technique has the characteristics of noncontact and nondestructive. A controlled air flow laser detection (CAFLD) method was proposed, which was based on the highprecision detection of micro deformation by laser, flexible onoff control and noncontact of the air flow. Five components were included in the air flow laser detection platform: laser ranging system, air force generation system, lifting testing bed system, force sensing system, and control and information processing system. The feasibility of chicken breast tenderness detection by using the CAFLD technique was explored. Three modes: transient (dynamic), creeprecovery (static) and stress relaxation (static) were adopted. The support vector machine and global variable partial least square algorithm were used to qualitatively identify and quantitatively predict the tenderness of chicken breast. The results demonstrated that the three modes combined with different preprocessing algorithms could carry out the qualitative discrimination of chicken tenderness, in which the transient mode had the best classification effect compared with the static modes. S-G convolution smoothing algorithm showed the best preprocessing performance. The classification accuracy (tender or hard) of the calibration set was 1 and 0.98, respectively, the Matthews correlation coefficient was 0.97; the classification accuracy (tender or hard) of the verification set was up to 0.95 and 0.84. For quantitative prediction of chicken tenderness, the S-G convolution smoothing algorithm was the optimum on improvement of the signaltonoise ratio. The transient had the best prediction effect, the correlation coefficients of calibration set and validation set were 0.948 and 0.913, respectively, the root mean square error was 0.736N and 1.013N, respectively. Because tenderness was the quality of meat which was shown by the difference muscle fiber structure. it can be inferred that the dynamic mode was more suitable than the static mode in predicting the quality caused by tissue structure. The application of CAFLD technique in meat quality multimodal evaluation was researched. It would provide a new solution method in meat detection field, and also had important reference significance for broadening the application field of the CAFLD technique.

Abstract:In order to quickly and nondestructively detect the content of whole potato powder in potato noodles, the hyperspectral imaging technology was used to quantitatively detect the content of whole potato powder in noodles. Totally 120 noodle samples with a total potato flour content of 0~35% were selfmade, and hyperspectral images of the noodles were collected in the 900~2500nm spectral range. Totally 80 samples were randomly selected as the calibration set, and the original spectra and the spectra preprocessed by moving average, smoothing S-G, baseline, normalize, standard normalized variate, and multiplicative scattering correction were used to establish the partial least squares regression model, principal component regression model and support vector machine regression model. The results showed that the partial least squares regression modeling effect was the best after the standardized preprocessing method. The coefficient of determination of the calibration set (R2C) was 0.8653, the coefficient of determination of the cross validation set (R2CV) was 0.6914. The characteristic wavelength was extracted from the spectral data preprocessed by normalize by regression coefficient method, and a simplified model of potato powder content PLSR was established. The coefficient of determination of the calibration set (R2C) was 0.8685. The validation set determination coefficient (R2CV) was 0.8021. The results showed that the model based on the characteristic wavelength was better than the fullband model. Using the remaining 40 samples as the prediction set, the NormalizePLSR simplified prediction model was established based on the characteristic wavelength. The coefficient of determination of the prediction set (R2P) was 0.8456. The model had good prediction ability. The results showed that it was feasible to use hyperspectral imaging technology to detect the total potato flour content in noodles.

Abstract:The storage of sweet potato is susceptible to chilling damage, which not only affects its quality but also is susceptible to other diseases, which greatly reduces the commercial and economic value of sweet potato. For the biological detection technology and traditional detection methods will cause irreversible damage to sweet potato, so a nondestructive detection method of sweet potato chilling damage based on optical fiber spectroscopy technology was established. The feature spectrum bands were selected by the key feature ranking method based on the class separability criterion. And the support vector machine algorithm was used to train and evaluate the data set to detect the accuracy of the characteristic spectrum and the occurrence of sweet potatoes before the symptoms of chilling damage were visible to the human eyes. Totally five sweet potato varieties were used for experiments. The accuracy of detecting chilling damage in sweet potatoes was as high as 99.52% with the ratio of training data and test data of 5∶5, and the incidence of the ratio of 7∶3 was as high as 9963%. The results proved the correctness of the characteristic spectrum, and the characteristic spectral bands were as follows: Jishu26 was 821.3~823.5nm; Yanshu25 was 810.5~821.9nm; Xiguahong was 8188~821.9nm; Xinong431 was 601.5~606.4nm; and Longshu9 was 759.6~761.2nm. The results showed that the spectroscopy technology can effectively detect and identify sweet potato chilling damage. This research provided technical method for subsequent work for sweet potato storage classification. 

Abstract:Aquatic products are easy to be corrupted and deteriorated after fishing. However, due to the large volume, inconvenient movement, and complicated operation, it is difficult to be applied for conventional detection devices. In order to meet the needs of rapid detection of aquatic products, a portable multiquality parameter detection device for aquatic products based on Raman spectroscopy was developed. The hardware system of the device was mainly composed of a light source module, a spectrum acquisition module, a system control processing module, a touch screen, a power module, and a communication module. The Raman spectral data of samples collected by the hardware system of the device, and the collected spectral data was smoothed and background subtracted by standard normal variate transformation, Whittaker smoothing algorithm, adaptive iterative reweighted penalty least squares algorithm. At the same time, according to the national standard method, the standard physicochemical values of pomfret color b*, thiobarbituric acid (TBA) and total volatile base nitrogen (TVBN) were collected, combined with spectral data, partial least squares regression quantitative prediction model for aquatic product quality was established. The results showed that the correlation coefficients of the validation color of b*, TBA and TVBN were 0.907, 0.897 and 0.915, respectively. The root mean square error of the verification set was 1315, 0104mg/(100g) and 2875mg/(100g). The prediction model was implanted into the portable device software system to realize onekey detection of multiquality parameter indicators of aquatic products. Finally, the accuracy of portable device was verified. The correlation coefficients between the predicted values of b*, TBA and TVBN of 18 pomfret samples and standard values were 0.927, 0.883 and 0.904, and the root mean square errors were 1139, 0271mg/(100g) and 1896mg/(100g), respectively. The results showed that the portable device can realize the multiindex realtime nondestructive detection of pomfret.

Abstract:In the spectral detection of livestock products quality and safe, the thickness difference between different samples leads to the difference in the distance between the meat surface and the optical fiber probe, which has a great influence on the prediction results. Aiming at this problem, an optical sensor for nondestructive detection of meat was designed, and the quality of pork (Longissimus dorsi muscle) was detected from the bottom to the top through the glass, which eliminated the influence of sample thickness on the detection distance, and the variation law of spectral curve with the change of detection distance was also analyzed. In order to explore the feasibility of the design scheme, a test platform was set up, including spectral acquisition unit, distance control unit, light source, glass, optical sensor and computer. The quartz glass can pass through the wavelength range of 220~2500nm without absorption. And optical sensors can help collect more diffuse light from the meat. Eighteen pork samples were stored at 4℃ and taken out at different refrigeration times for spectral collection (400~1100nm) with different detecting distances in the range of 8~22mm at approximately 2mm intervals. Finally, the TVBN content of the samples were measured. After obtaining the spectral data of the samples, the methods such as first derivative, multiplicative scattering correction (MSC), standard normal variate (SNV) and first derivative plus SNV were used to pretreat the spectral data of the samples, and the partial least squares regression (PLSR) prediction model of the content of pork’s TVBN was established. The results showed that when the detection distance was 16mm, the prediction model of pork’s TVBN using the 1st DER plus SNV preprocessing method had the best prediction effect. The correlation coefficient and RMS error of correction set were 0.98 and 0.92mg/(100g), respectively, and the correlation coefficient and RMS error of prediction set were 0.97 and 1.56mg/(100g), respectively. Therefore, it was feasible to detect pork freshness with the designed optical sensor.

Abstract:Targeting on the demand of the market for apple quality detection, a handheld device for apple sugar content detection combined for mobile phone based on visible/near infrared spectroscopy technology was designed to determine the wavelength range and spectral sensor suitable for apple sugar content detection by optimizing the characteristic wavelength. The combination with the mobile phone completed the highefficiency, nondestructive and lowcost detection of apple sugar content. An STS-NIR miniature fiber optic spectrometer (wavelength range 650~1100nm) was selected to collect the spectra of 120 apples by using the spectrum acquisition platform built by the laboratory itself, and the true sugar content of the measured apples was obtained through the sugar refractometer. The partial least square (PLS) algorithm was used to model the fullwavelength data, and variable selection methods such as successive projection algorithm (SPA), genetic algorithm (GA) and competitive adaptive reweighted sampling method (CARS) were used to identify and simplify the characteristic bands of the fullwavelength to select the effective wavelength. Variables of the measured wavelength, and the effective wavelengths were selected according to the regression coefficient. The results of variable selection showed that the three sets of characteristic variables obtained had overlapping terms, and all of them contained wavelength variables related to the apple sugar content. The partial least squares (PLS) algorithm was used to establish a prediction model of apple sugar content based on three sets of characteristic bands variables, and the three sets of results were analyzed, including the comparison of prediction correlation coefficient (Rp), prediction root mean square error (RMSEP) to evaluate the accuracy of the built model. The experimental results showed that the modeling results obtained by using the three groups of characteristic were all good, and the predictive correlation coefficient was above 0.93, among which GA-PLS model had the best predictive effect on apple sacchariness, with the predictive correlation coefficient up to 0.9447. According to the highly overlapping coincidence term of the characteristic variables bands obtained above, the characteristic wavelength bands and their corresponding optical sensor for detecting apple sugar content saccharification were determined, and 40 other apples were tested and verified based on the designed handheld device for testing the sugar content of apples. The correlation coefficient was predicted to be 0.8822 based on the designed a handheld device for apple sugar content detection combined for mobile phone. The results showed that the device designed was of low cost, easy to carry and had high detection accuracy and efficiency, and it was feasible to realize the realtime nondestructive testing of apples sugar content. 

Abstract:Pomelo is an important fruit of citrus. The high fiber content of pomelo peel can be used as a good raw material to extract pomelo peel cellulose. Using pomelo peel cellulose (PP-C) as the raw material, the pomelo peel nanomicrocrystalline cellulose (PP-NCC) was prepared by sulfuric acid hydrolysis method. The micromorphology, aspect ratio, infrared spectrum, crystallinity, and thermal stability of the PP-NCC were analyzed. The effect of PP-NCC on the rheological properties of carboxymethyl starch filmforming fluid was studied. It was found that the PP-NCC was a rodshaped crystal with an aspect ratio of 8 to 20, and the proportion of aspect ratio greater than 10 was over 60%; the main substance of PP-NCC was cellulose; the crystallinity of PP-NCC was increased from 55.64% before acidolysis to 74.35%, and its initial thermal decomposition temperature was decreased from 240℃ to 212℃. PP-NCC could be used as the reinforcing agent of carboxymethyl starch film. According to the equation, the rheological index was less than 1, indicating that pomelo peel nanomicrocrystalline cellulose/carboxymethyl starch film forming fluid was pseudoplastic fluid. G′ of the film forming liquid was greater than G″, and no crossover occurred between the two within the frequency scanning range, showing that the composite film forming liquid was of weak gel structure. The viscosity coefficient KPL in static rheological parameters, the zero shear viscosity and the energy storage modulus in dynamic rheological parameters were positively correlated with the addition of nanocrystalline cellulose, showing that the dispersibility of PP-NCC in the filmforming liquid was good, which was helpful to strengthen the interaction of the internal structure of the filmforming liquid. The nanofilm of pomelo peel fiber showed better functional properties and can be used as a significant direction for comprehensive utilization of pomelo peel. 

Abstract:Research on ovine meats intelligent segmentation remains limited because of the low recognition accuracy of target muscle region image caused by preprocessing process. A method of target muscle region recognition in ovine hind leg intelligent segmentation based on R2U-Net and dense atrous convolution algorithm was presented. The traditional U-Net semantic segmentation network was taken as the backbone network and improved. The convolution blocks in the feature encoder and decoder of the original U-Net were replaced with the residual recurrent convolution blocks to avoid the gradient loss of the U-Net and a four branch dense atrous convolutional module was added between the feature encoder and the feature decoder to code multiscale semantic features. On the one hand, aiming at the sartorius muscle region, the ovine hind leg images were collected to build a dataset and the model was trained and tested using the dataset to validate the accuracy and realtime performance of this method; on the other hand, the homogeneous transformation matrix of gripper coordinate system, camera point clouds coordinate system and robot coordinate system was calibrated based on screw theory to calculate the segmentation path, and the robot cutting manipulation was controlled by an active compliant force/position hybrid control method, which validated the feasibility of target muscle segmentation based on the target image obtained by this method. The experimental results showed that when the intersection over union (IOU) was 0.8588, the average precision (AP) of the proposed method was 0.9820, which was better than that of R2U-Net (0.8324, 0.9775); the average time of single sample detection was 82ms, which showed that this method can segment the sartorius image quickly and accurately, which met the realtime requirements of robot autonomous segmentation system, and it was better than U-Net, R2U-Net and AttU-Net algorithms. Finally, based on the image of sartorius muscle obtained by this method, the real robot segmentation experiment was carried out. The average time of robot cutting on five sheep hind legs was 7.9s, the average offset distance was 4.36mm and the maximum offset distance was not more than 5.90mm, which met the accuracy requirements of sheep hind leg boneless segmentation.

Abstract:As wheeled tractors are widely used as power machinery in agricultural activities, the lateral stability of a tractor directly affects the operation efficiency and machine safety with worldwide inevitable rolloverinduced injuries and fatalities. From the perspective of active safety control, this article aims to apply the reverse moment of an accelerating momentum flywheel to the rolling tractor. In this study, we analyzed the evolution mechanism of the tractor dynamic overturning behavior by mathematical modeling. In order to keep the original configuration of the main structure of the tractor, the momentum flywheel was installed in the tractor front to replace the conventional static ballast, while it actively provided the antirollover torque in emergency cases. Using Matlab/Simulink, the simulation work on the effectiveness of the PID speed control was carried out. Furthermore, a scalemodel experimental platform was designed to verify the flywheelbased tractor active stability control system. The results showed that the tractor equipped with a flywheel was able to regain lateral stability repeatedly in one experimental run. The test data under different driving conditions were compared with the uncontrolled group verifying the effectiveness and accuracy of the tractor dynamic model and the active control algorithm proposed in this paper. The proposed approach potentially provides theoretical basis and technical support for the extension of tractor active stability control technology. 

Abstract:In order to optimize the design of tractor cab seat, reduce the workload of the driver, improve work efficiency, and solve the problem of insufficient technical basic research on the comfort of cab seat of Chinese tractors, evaluation method for seat comfort of tractor cab based on bone joint recognition was proposed. Firstly, based on the analysis of factors affecting the comfort of tractor seat, the human sitting joint angle was selected as the research factor. The consumergrade depth camera Kinect v2 was used to conduct eight driving motion capture experiments on two tractors equipped with different seats. The joint angle information with an accuracy of 0.01° under different driving actions was obtained; then, the joint angle data was imported into the human body modeling simulation analysis software Jack to obtain the human body model, and the joint torque simulation and lower back force were carried out according to different driving actions simulation and analysis to obtain the results of human comfort; finally, based on the analytic hierarchy process, a hierarchical model of the tractor seat comfort evaluation index was constructed, the weight of each index was determined and the consistency test was performed, and the original data of all the indicators involved were processed and calculated to obtain the comprehensive evaluation result of seat comfort. The simulation results showed that compared with tractors with ordinary seats, when working on tractors equipped with ergonomic seats, the ability of digital humans to complete actions was increased by 10 percentage points, and there was no joint discomfort. The pressure can be effectively reduced by 80N in the driving posture and 370N in the twisting posture, and the lateral shear on the waist was also reduced, proving that the digital human was more comfortable on this tractor seat. By analyzing the seat comfort evaluation matrix, it can be obtained that the seat comfort designed according to ergonomics was better than ordinary seats. The evaluation results based on the bone joint recognition method were consistent with the results analyzed based on the analytic hierarchy process, which proved the feasibility and effectiveness of the tractor cab seat comfort evaluation method based on bone joint recognition. This evaluation method can provide certain reference basis and guiding countermeasures for the ergonomics research of tractor cab seat and the accurate and efficient optimization of tractor seat design. 

Abstract:Considering different power requirements of the tractor under various working conditions, the singlemotor powertrain system is usually in low load state under low load working conditions, with low efficiency, resulting in energy waste. To solve this problem, a dualmotor multimode coupling driving system for electric tractors was proposed. Through the coordinated control of two motors and brakes, four driving modes could be realized: motor EM_S independent drives, motor EM_R independent drives, dualmotor coupling drives and dualmotor independent drives. These modes could meet the tractor power demand under various working conditions, improve the load rate of motor, and thus improve the efficiency of the whole vehicle. A parameter matching method was proposed to match the parameters of the two motors and the main transmission ratios of the coupling box according to the dynamic performance indexes of the typical working conditions. In order to realize the efficient operation of DMET, and enhance the adaptability of the energy management strategy to different operating conditions of electric tractors, a realtime energy management strategy based on stochastic dynamic programming + extreme seeking algorithm (SDP_PESA) was proposed. The state feedback control table generated offline by SDP as the control input reference was used to ensure the approximate global optimum. On this basis, the adaptive optimization algorithmPESA was introduced to dynamically search the local maximum value of the system output to compensate for the control input of SDP and generate operating points with lower energy consumption and higher efficiency. The EMS based on SDP_PESA considered the good optimization performance of the global optimization algorithm and the robustness of the instantaneous optimization algorithm comprehensively, and the advantages of the two algorithms were used to achieve more excellent control performance. A DMET simulation model with SDP state feedback control table was established based on Matlab/Simulink, and real operating conditions were used to simulate the energy management strategies based on SDP and SDP_PESA. The simulation results demonstrated that the actual vehicle speed can track the change of the target vehicle speed in real time, and the control strategy can quickly respond to the change of the work load, indicating that the DMET simulation model was efficient and feasible, and can meet the simulation accuracy requirements. Based on the energy management strategy of SDP, the average power consumption of DMET in plowing and transportation conditions were respectively 1.77kW·h/km and 1.17kW·h/km, the driving efficiency was 0.80 and 0.81, respectively. However, after adding the PESA output feedback controller, the driving efficiency was increased by 213% and 197%, and the average power consumption was reduced by 10.17% and 16.2%, respectively, which meant the energy management strategy based on SDP_PESA can effectively increase the operating range of pure electric tractors, and SDP_PESA was fully capable of realtime application.

Abstract:In view of the diversity of crops in the Huang-Huai-Hai area, the row spacing is large and the plant protection machinery is low in generalization and intelligence. A articulated steering unmanned plant protection vehicle with adjustable wheelbase and ground clearance was designed. The plant protection vehicle can be remotely controlled by a remote control, and after switching the automatic mode, it can track the path according to the predetermined route to realize the autonomous walking of the plant protection vehicle. A kinematics model was established for the autonomous walking mode of the plant protection vehicle, and the strategy of using heading tracking to realize the path tracking was determined, and the stability of the waist turning control was analyzed through the Lyapunov function. The extended Kalman filter algorithm of the sensor and the PID control method of the drive motor were proposed. Finally, the step response of Matlab was used to simulate and analyze the autonomous walking control system. The results showed that when the coefficients Kp=1，Ti=0.05,Td=0.01, the system response speed and accuracy can meet the needs of autonomous plant protection vehicle navigation control. Field tests were conducted with the turning radius of the work platform and the offset parameters of straightline walking. When the turning speed of the prototype was 3km/h, the minimum outer wheel turning radius was 2m, and when the walking speed was 6km/h, the average offset for 100m straight travel was 5.51cm, and the average endurance time of the plant protection vehicle under full load was 2.54h. The whole machine met the design requirements.

Abstract:With the aim to solve the problems of low identification accuracy of the front tractor, relative positioning difficulty, and difficulty in ensuring the safety of autonomous operation in the multimachine coordinated navigation operation, a method of tractor identification and positioning based on depth image and neural network was proposed. The tractor features were recognized and extracted by establishing YOLO-ZED neural network recognition model. The ZED camera was used to collect 1100 tractor images at different angles, distances, and resolutions in cloudy and sunny days, and the LabelImg marking tool was used to manually mark the collected tractor images, marking the cab as the identification target. The tractor positioning model based on the depth image was established and the binocular positioning principle was used to calculate the spatial position coordinates of the tractor relative to the machine. A fixedpoint identification and positioning test was performed on a small power tractor, and the identification and positioning results of the tractor were measured along the longitudinal, width and Scurve directions of the tractor. The test results showed that the algorithm can quickly and accurately identify and locate the spatial position of the tractor, and the average identification and positioning speed was 19f/s. The maximum absolute error of positioning the tractor in the camera depth direction and width direction was 0.720m and 0.090m, respectively, the maximum relative error was 7.48% and 8.00%, and the standard deviation was less than 0.030m. The accuracy and speed requirements of tractor target identification for multimachine coordinated navigation can be met.

Abstract:To improve the agricultural mechanization rate，an entiretrack modular unmanned agricultural power chassis with reasonable cost and convenient maintenance was presented based on the structure of the traditional articulated mountain tractor drive train for the unstructured roads such as mountains and hills and the complex and diverse crop growth environment. Meanwhile, in order to improve the passing performance and stability performance, the structure and topology optimization analysis of the crawler walking device base frame and the driving wheel support of chassis walking system were carried out. Furtherly, the quickconnect device of the farm implements mounting module and the threepoint linkage with PTO were designed. The quickconnect device can be used to replace different attachments to achieve different operations of the whole machine to improve the utilization rate of the whole machine. The differential steering device with motor compensation power can realize insitu steering and improve the mobility of unmanned agricultural power chassis. Finally, the digital automation transformation was realized for the future intelligent manufacturing. 

Abstract:The output power of diesel engine is one of its important performances. For the individual components of an engine, the accurate output power can be measured through the dynamometer. However, it is not easy to accurately measure the output power of the diesel engine during tractor ploughing. Based on the torque model of the diesel fuel control strategy, the output power of the diesel engine was measured online during the Lovol tractor ploughing process with the theoretical speed of 5.7km/h and 8.9km/h. The indicated power of the torque model was compared with that of the combustion analyzer. The test results showed that when the tractors ploughing speed was relatively stable, the error of the average value of the indicated power was 2.99%, but the instantaneous value became distorted seriously. It was found that the changes in the fuel injection amount and the injection timing are the main reasons for the large deviation in power measurement. To improve the accuracy of the online measurement for diesel engine output power, the quantitative relationships between the fuel injection quantity, fuel injection time and torque under 12 typical working conditions were obtained by using the GT-Power model. Then, the correction coefficients of fuel injection quantity and fuel injection time were used to optimize the original measurement method. The optimized results showed that under the stable operation, the average measurement error of diesel engine output power is 0.88%, and the instantaneous value’s error was reduced significantly. It can be learned that optimizing the fuel injection strategy of the diesel engine is an important way to improve the performance of the diesel engine during tractor ploughing. 

Abstract:Based on the urgent demand of modern agricultural development for micro near infrared (NIR) spectrometer, the experimental research on the core component of the NIR spectrometer was carried out. To overcome the problems of high driving voltage, small scanning angle, etc., the structural optimization and improvement of driving system for the electromagnetic MOEMS scanning grating mirror was proposed. By using the professional simulation software Maxwell 16.0 to optimize the magnetic field of the permanent magnets with different sizes and material properties, the NdFeB with different grades of N38 and N52 was obtained as the working permanent magnets. On this basis, two electromagnetic MOEMS scanning grating mirrors marked A1 and A2 with the same size were designed and fabricated, which were used to combine with the two permanent magnets respectively for performance test. The test results showed that compared with the permanent magnet N38 with weak magnetism, when the two electromagnetic MOEMS scanning grating mirrors combined with N52 reached the maximum mechanical scanning half angle, the driving voltage was decreased by 6.6% and 8.6%, and the maximum mechanical scanning half angle was increased by 20.2% and 17.4%, respectively. Through the comparison and analysis of the mechanical and electrical performance test results, it can be concluded that the structural improvement of the driving system can effectively improve the performance of the MOEMS scanning grating mirror, and it had important practical application value for improving the spectral detection range and accuracy of the NIR spectrometer. 

Abstract:Composite gradient plates with GCr15, Q420 and IF steel was fabricated by vacuumrolling composite (VRC) technology and the forage harvester blades were prepared. Microstructure, chemical composition and hardness distribution, and shear strength in the interface of composite gradient plates were inspected. In order to compare the cutting performance between composite gradient material selfsharpening blades and commercial blades, the field experiment was carried out. The results indicated that a more disordered metallurgical bonding characteristics because of materials interbiting characteristics at the interface of different plates (GCr15/Q420, Q420/IF) during rolling process was formed. With fewer microstructure defects, transition zone was formed due to the chemical compositions diffusion in the interface. The shear strength of the bonding interface exceeded the requirements of the national standard, which can meet the requirements of gradient material selfsharpening blades. The interface fracture mode was ductile fracture with good plasticity. There was a relatively gentle hardness gradient variation between different interfaces. The flank surface, point tip and cutting edge of selfsharpening blades were made up of GCr15 steel with higher hardness and wear resistance. Hardness gradient variation and uniform wearing for rake surface of selfsharpening blades were remarkably exhibited. In the operation process, selfsharpening blades improved the operation efficiency and service life. It can keep the tool tip in the prominent position and edge curvature radius slightly change, which can maintain sharpness property of blades and lowdamage cutting of regeneration. Field experiment can obtain the results comparison of wear weightloss rate and macroscopic morphology between the composite gradient material selfsharpening blades and commercial blades. The results showed that under the same operation conditions, compared with commercial blades, the gradient material selfsharpening blades had more excellent properties: slightly variation of arc radius, edge curvature radius, and abrasive resistance. The further field experiment results indicated that the wear resistance of the selfsharpening blades was more than three times of that of commercial blades. 

Abstract:A biomimetic microtexture tool for earthworm was designed. Based on the surface morphology of earthworm, the microtexture of tool surface was processed by laser molding technology. The friction coefficient and wear of the bionic texture tool and the ordinary tool were studied through the comparative test of friction and wear, and the wear reduction mechanism of the bionic tool was analyzed. The cutting test of longan branches with different diameters was carried out by the selfmade cutting test platform to verify the wear reduction characteristics of the bionic cutting tools. The results showed that the optimized process parameters of the bionic laser forming tool were as follows: laser power was 75W, laser scanning speed was 4.8mm/s; the actual size of the microtexture of the bionic cutter was 138.3m wide and 33.5m deep. Compared with ordinary cutting tools, the texture bionic cutting tools showed the minimum friction coefficient of 0.2619 and the volume wear amount of 616.70mm3 when the groove spacing width was 1.6mm under the load of 400g, which had obvious wear reduction characteristics. With the increase of load, the wear mechanism was gradually changed from adhesive wear and microcutting wear to the complex wear forms of abrasive wear and oxidation wear. When the wear was stable, the required cutting times of 1.6mm texture bionic tool were 50~55 times higher than that of ordinary tool (45~50) times, and the stable times of 1.6mm texture bionic tool in cutting the wear area of branches with a diameter of 10mm, 15mm and 20mm were 35~40,45~50 and 50~55 respectively. The larger the diameter of the branch was, the more obvious the antiwear effect of the texture tool was.

Abstract:Aiming to meet the technical requirements of largeload helicopter, the spherical plain bearing of its rotor system has better antiwear capability, wearreduction and high bearing capacity in the complex working environment, so as to improve the life performance index of the bearing. A selflubricating spherical plain bearing used in the rotor system of a new type helicopter with large load was studied. CrDLC and WDLC film coating, were prepared on the surface of 9Cr18 inner ring substrates of spherical plain bearing by unbalanced magnetron sputtering. The microstructure, friction and wear properties and wear scar morphology of two kinds of thin film coatings were tested and analyzed by scanning electron microscopy, threedimensional topography, balldisk friction and wear tester and low speed heavy load friction and wear tester. The results showed that the friction coefficients of the two film coatings were increased gradually at the beginning of the friction stage. With the progress of the friction process, the friction coefficients tended to be stable and kept fluctuating in a certain range. Compared with 9Cr18-CrDLC specimens, 9Cr18-WDLC specimens had shorter stability time of friction coefficient, more stable overall friction process and lower friction coefficient, showing better friction performance. Compared with 9Cr18-CrDLC specimens, the wear process of 9Cr18-WDLC coating and selflubricating liner was relatively stable, the friction coefficient fluctuated in a small range, the overall wear scar was shallow, the overall wear volume was small, showing good wear resistance. The tribological properties showed that WDLC film coating had better wear resistance and antiwear properties for 9Cr18 substrate material. 