Abstract:Fruit nondestructive picking is one of the key technologies of developing harvesting robot. A nondestructive picking end-effector of kiwifruit was studied. Firstly, based on the artificial way of kiwifruit picking and the biology characteristics of kiwifruit stem, a fruit picking method for robot was proposed, which need to separate the fruit from stem and hold the fruit to prevent it dropping. Then, the picking method was verified by a special designed separation test of fruit and its stem. After that, an end-effector was designed and manufactured based on the fruit picking method, which approached a fruit from the bottom, and enveloped and grabbed the fruit from two sides, and then rotated up to separate the fruit from stem. In the end, the performance of end effector prototype was tested on the most common cultivar ‘Hayward’ at the Meixian Kiwifruit Experimental Station of Northwest A&F University. The results showed that the proposed picking method could separate the fruit successfully with the least force of 1.3N when the angle between fruit and stem was set as 60°, which is not significantly different from the manual picking of which the angle between fruit and stem is approximately to 90° in normal. The end effector was tested on 68 samples (28 in the morning, 25 in the noon, and 15 in the night). All of them were successfully picked and held by the end-effector. Among them, two samples were picked with stem which might be caused by the reason of that the fruit is not ripe enough to be harvested. All the picked fruit were free of damage until ripen for eating. In all, the end effector could effectively solve the problems of separating the adjacent fruits, grab a single fruit with an accuracy of 100%, and pick and hold it nondestructively. The success rate of picking was 96.0% and the average picking time was 22s.

Abstract:Early fruit-yield forecasting plays an important role in productive and sustainable management of apple orchards. This paper presents a method combining image processing with support vector machine (SVM) technology to build a prediction model for early season apple tree yield estimation. Sixty ‘Gala’ apple trees were randomly selected for study. Initially, tree canopy images were captured in natural light just after June drop when the fruit color was green. Apples in the canopy image were identified with the condition Cb≤100 and Cr≥120 obtained by analyzing the distribution map of color component values in YCbCr color space, in which Y was the luminance component, Cb and Cr were the blue-difference and red-difference chroma components. By the same method, the condition Cr≤125 was used to segment foliage from canopy image with fruit removed. Five characteristics were extracted from the canopy image: fruit total area, total number of fruit, proportion of fruit total area to foliage area, proportion of total fruit area shaded by leaves to total fruit area, and proportion of total fruit numbers shaded by leaves to total fruit number. Finally, the SVM method was employed to build a yield estimation model with these five characteristics as input parameters and the actual yield as output. A randomized sample set containing 50 trees was used to train the model, yielding a coefficient of determination (R2) of 0.7242, a root mean square error (RMSE) of 1.71kg, a mean absolute percentage error (MAPE) of 9% and an average prediction error (MFE) of 0.21. Using 15 independent samples, the model was validated, yielding a RMSE of 2.45kg and a MAPE of 13%. The proposed model showed significant potential for early apple yield prediction of individual trees with potential application to other fruit crops.

Abstract:The paper presents a method of image recognition for apple picking robot at night. In the stage of image acquisition, comparing different lighting effects of light source, the proposed method selected the incandescent lamp as artificial lighting. And two lamps were placed in different sites to weaken shadow with 60° angle. In the stage of image segmentation, comparing the image recognition methods adopted in daytime, the improved R-G image recognition method was proposed. Referring to reflective areas in the surface of apples, twice segmentation method was proposed to separate reflective areas from images to repair segmented images above. The first segmentation aimed to determine the areas in where apples were located. The second segmentation aimed to determine the reflective areas in the determined areas of first segmentation. Taking no account of sheltered and adhesive apples, the rate of identification on the basis of the statistic of 60 images acquired at night can reach to 83.7%. This paper verified the ability of image recognition for apple picking robot at night and discussed the feasibility of apple picking at night.

Abstract:The image segmentation algorithm based on the fuzzy C-average clustering (FCM) needs initial cluster number and cluster center in advance, which make the algorithm easy to fall into local optimum. An image segmentation method based on improved artificial swarm optimization fuzzy clustering was proposed. The optimization of proposed method was conducted on the basis of the traditional artificial colony. The fitness function of artificial colony was improved by using objective function of FCM algorithm. With the collaboration of bee colony, follow bees and computerized bee, the optimal initial clustering center could be solved quickly. Then the optimal initial clustering center was input into FCM and image segmentation was finally realized by using maximum membership principle. The fruit segmentation experiment was carried out with 300 ‘summer black’ grape photos taken under frontlight, backlight and normal light illumination conditions. The experiment proves that the proposed method can identify fruit from the natural environment quickly. The average time for segmentation was 0.2193s per photo and accuracy was 90.33%. The time consuming was shorter and the accuracy was higher than OTSU and traditional FCM algorithm. It can meet the real-time requirement of picking robot and fruit grading system.

Abstract:Taking agricultural vehicle with machine vision navigation as study object, a self-adaptive fuzzy control method with improved particle swarm optimization algorithm was designed. Firstly，by establishing 2-DOF steering model and visual preview model, lateral control equations of vehicle were described. Secondly，in order to improve the convergent speed of particle swarm optimization (PSO) algorithm，an improved PSO algorithm was designed. Finally, agricultural vehicle guidance system was a complex system with high nonlinearity, time-varying and large delay; therefore, an adaptive fuzzy controller was used for path tracking control. Correction factors were introduced into the fuzzy controller and particle swarm algorithm was used to optimize the correction factors. Taking the integral time absolute error (ITAE) sum of lateral offset and heading offset as the objective function, optimal correction factors were calculated by using PSO algorithm. Simulation and experimental results showed that the designed control algorithm could eliminate the lateral offset rapidly with less overshoot and rapid response. It retained the advantages of fuzzy control method and improved the control quality of guidance system. Compared with standard fuzzy control method, the improved fuzzy control method has a significant improvement on navigation accuracy under the same parameters condition. When the velocity of vehicle was 0.8m/s, the maximum lateral offset of straight path and curve path were less than 4.2cm and 5.9cm respectively, which could meet the requirement of agricultural vehicle navigation.

Abstract:Four-wheel independent drive agricultural vehicles are widely used in facility agriculture and animal husbandry of material transportation and information collection, but the navigation and control are difficult. A navigation and control method based on optimized information fusion of multiple sensors was proposed. The proposed system was consisted of CCD, acceleration sensor, electronic compass and ultrasonic. The marked path information was obtained by using CCD. The vehicle posture information was got by using acceleration sensor and electronic compass. And the obstacles were judged by using ultrasonic sensor. Meanwhile, several algorithms were presented, including extraction of road signs feature, multi-source information fusion and ultrasonic obstacle avoidance algorithm. The proposed system can identify and avoid obstacles automatically. On the basis of above, a fuzzy control system was adopted to accomplish the car navigation path tracking control. The experimental results show that the method of information fusion and navigation control is correct and effective.

Abstract:Variable universe fuzzy controller was designed for guaranteeing the quality of full hydraulic steering control on Dongfanghong-LX854 tractor. The basis fuzzy controller was designed according to the characteristics of the system. The optimal basis fuzzy control parameters under different waveforms and amplitude excitation signals were obtained by using rotation up optimization method in Simulink software. The adaptive fuzzy controller parameter turning changed the system to be an optimal control system by adjusting the universe in the basis fuzzy controller according to simulation results. The windowed Fourier transform and self convolution were used to design online identification system. The experiment results on the Dongfanghong-LX854 tractor indicated that the variable universe fuzzy controller was better than the invariable universe fuzzy controller. The measured 20° step response indicated that the regulation time was 2s, the largest steady error was 0.18°, and the response without steady state oscillation. The measured sine response showed that the average delay was 0.3s. The variable universe fuzzy control system lays a foundation for 2BFQ-6 precision planter navigation.

Abstract:A dual-differential-driven mobile robot is consisted of two differential driving modules equipped with normal-shape wheels, suffering from constraints of nonholonomic and redundancy in motion. A two-input-two-output nonlinear kinematics model was established for path tracking of the proposed mobile robot and then linearized by the approach of input-output linearization. The need for coordinating the speeds of two driving modules was analyzed when considering the redundancy in motion, and a hybrid control law combining an evaluation function method of error intelligent-transformation with an approach of exponential stability control was proposed. The evaluation function method was used to compute the suitable control output intelligently for different error states so as to convert them into the applicable range of exponential stability control. Then the latter was used to eliminate posture angle error and distance error synchronously towards zero. The results of digital simulation and experiment test showed that the hybrid control law could transform error states smoothly and eliminate two pose errors synchronously, and the mobile robot could track the linear and circular guide paths accurately and steadily.

Abstract:Variable spray is one of the important ways for precision applying pesticide. In the past decade, great progress has been made in the technology and applications of variable spray. A comprehensive review of current research was presented in following categories: detection technology of variable spray system, control technology of variable spray system, and integration of spraying system. On the detection of crop morphology and density, ultrasonic method for detecting crop morphology was discussed and the error analysis of ultrasonic detection of crop morphology was carried out, the characteristics of ultrasonic technology and laser technology used in crop morphology detection were compared, and the advantages of LIDAR (Laser imaging detection and ranging) used for the detection of structural characteristics and canopy of trees and the superiority of LAI (Leaf area index) introduced to characterize the crop density were specially emphasized. On the detection of crop diseases, insect pests and weed, and the features of some information analysis techniques such as SOM (Self organizing maps), ANN (Artificial neural networks) and SVM (Support vector machines) etc. used for detecting crop diseases, insect pests and weed were summarized. A point was emphasized that the characteristics of crop cultivation and management should be combined with the detection of crop diseases, insect pests and weed. In terms of variable spray servo system, the existing variable nozzle and its control technology was generalized, and using the control technology to improve the performance of low cost devices and equipments was highlighted. Finally, the integration of spraying systems was also summarized and the development direction of the variable spray technology was pointed out.

Abstract:A dynamic PWM variable spray experiment platform was built up to solve the problems of discontinuous operation of nozzles in spray progress, and improve the homogeneity of droplets, especially homogeneity along the travel direction. This platform included high-speed solenoid valve, a stainless steel pressure tank, a pressure sensor, an air pump, a conveyor and so on. The distribution features of droplets in dynamic spray based on this platform was studied. Water sensitive paper was used to collect droplets under different frequencies and different duty cycles of PWM controlling signals, also different pressures of spray. Image processing technology was used to get the coefficient of variation (CV) value of percent area droplets coverage to evaluate the uniformity of droplets. The homogeneity of single nozzle dynamic spraying was evaluated under different experiment conditions. The research suggested that CV value decreased as the duty cycle of controlling signals increased, the frequency of controlling signals had influence on homogeneity, which was CV value decreased as the frequency increased. And what is more, when pressure became high, CV value became larger and the influence was weaker compared to the other factors.

Abstract:In order to identify the two characteristic lengths of breakup process of low-pressure jets, the relationship between different diameters and angles of entrance of jet nozzle on the breakup of low pressure jet under different pressures was studied. An experiment was conducted to investigate the core lengths and breakup lengths of a round water jet. The flow, ranges and ending raindrop diameters were measured under low jet velocity. The results showed that with the increase of nozzle diameter, the flow, ranges, ending raindrop diameters, core lengths and breakup lengths became larger. With the increase of nozzle cone angle, the flow became smaller, the ranges increased at first then decreased, the ending raindrop diameters increased and the core lengths decreased, but the breakup length decreased at first then increased. The ranges and the atomizing condition showed that the diameter of nozzle of 5mm and cone angle of nozzle of 45° were the best. Correlation equation was proposed based on the analysis of effect of Re and We on the core length and breakup length.

Abstract:A type 2BH-3 inter-row seeder for maize was designed to meet the agro-technical requirements of stubble mulching and row(ridge)-inter-row(furrow) tilling alternately, which can perform inter-row operations including fertilizing, seeding, covering and rolling at a time. In order to reduce the longitudinal length of the inter-row seeder, a multifunctional road wheel was designed, which can serve multiple functions such as land following, depth limit, transmission, soil covering, rolling and soil breaking. The discrete element simulation was conducted to compare the rolling effects of the two road wheels, one with a smooth inclined plane and the other with V-shaped ridges, by using EDEM software. The simulation results showed that the road wheel with V-shape ridges had higher ground pressure, making the porosity of soil decrease by 6.38%~6.93%. Field tests showed that the qualification rate of seed spacing was 89.8%, the miss seeding rate was 2.3%, the multiples rate was 7.9%, the average vertical distance between seed and fertilizer was 3.99cm, the coefficient of variation of instability of fertilizing between rows was 2.35% and the coefficient of variation of inconsistency was 1.62%.

Abstract:In the processing and winding process of corn directional belt making, tension control determines the quality of corn directional belt. A corn seed directional belt making machine was developed and transfer functions of constant tension winding system were set up. The fuzzy PID self-adaptive control technology was used to achieve constant tension winding in corn directional belt making and a fuzzy PID self-adaptive controller was created. Finally, the software Matlab was used to simulate. As a result, reasonable fuzzy PID self-adaptive control algorithm was obtained, and fuzzy PID self-adaptive control algorithm was used in the actual tension control by using Siemens S7-200 PLC core hardware control circuit, as well as the winding experiment was carried out. Test results showed that the fuzzy PID self-adaptive had better dynamic stability and tracking performance compared to the conventional PID controller and the controller could meet the requirements of corn directional belt winding. When the tension generated step, system transition time was about 2s and overshoot was in 1.2%.

Abstract:Main factors affecting the working quality of horizontal snapping roller of corn harvester when it snaps the corn ear were analyzed. By adjusting the spacing between two snapping rollers, the snapping rollers can adapt to corn stalks of different diameters, so the snapping rollers can hold the corn stalks tightly all the time. Finally, the blocks occur during corn harvester working were solved effectively. The grain losses of corn ears were reduced by adjusting the rotational speeds of snapping rollers differentially. Model of spacing-adaptive differential snapping roller was built by using CATIA, and its simulation analysis was conducted compared to the snapping rollers with fixed spacing by using ADAMS software. The optimal speeds of inner and outer snapping rollers were 900r/min and 860r/min which were determined by simulation test of ADAMS. At last, in order to certificate the analyses and design, the field test was conducted. There was no jam occurred during the field test, and the grain losses and damages were both far lower than the national standard which is 5%.

Abstract:In order to study the mechanism of sugarcane leaf sheath stripping using elastic dentation typed stripping element, the experiments of three-dimensional dynamic hitting force were conducted under the action of elastic dentation on sugarcane stalks. The specialized test bench was designed to fix the stalk at opposite ends by using two fixed components, and one way type piezoelectric impact sensors were respectively fastened on each fixed component. An elastic dentation driven by the rotating roller hit the middle of the stalk, and the dynamic hitting forces were measured in real time by sensors. After data processing, the maximum values of Fx, Fy and Fz in longitudinal, transversal, and tangential directions were obtained. Four factors including rotate speed of roller, interleaved depth and lateral offset distance between the elastic dentation and stalk, and material of elastic dentation were determined. Single factor experiments were carried out to analyze the effect of factors and obtain the maximum values of dynamic hitting forces in three directions with the optimal parameters combination. The formula of maximum failure force of leaf sheath stripping was deduced and the mechanical model of leaf sheath striping was established which combined with material mechanics properties and leaf sheath stripping criteria. The results showed that the tested maximum values of Fx and Fy were equaled to 93.87N and 138.26N which were greater than the maximum failure force of leaf sheath in x and y directions, 76.40N and 53.53N simultaneously, under the condition that the rotate speed of roller was 700r/min, the interleaved depth was 30mm, the lateral offset distance was 20mm, and the material of elastic dentation was polyurethane with shore hardness 85HA.

Abstract:For the purpose to improve the cleaning performance including reducing the losses and impurity rate of peanut picker and harvester with two-stages, based on the study results on the floating velocities of different extraction components of peanut pods, the cleaning principle and scheme with double air-suction inlets combined with vibration screen was put forward. The overall structure as well as the key parts of the proposed cleaning device was designed. And the cleaning device was developed and its performance test and study was conducted under peanut harvest production condition. The parts of pneumatic cleaning named double air-suction inlets contained the front suction inlet and the rear suction which worked separately step by step and together in two steps. The front suction inlet was close to the peanut picker which cleaned lighter materials such as the peanut fruit stalk and the peanut leaf, and the rear suction inlet was close to the discharge port which cleaned immature peanut pods and the crushed stems. The tested results showed the floating velocity of different extraction components of peanut picked gained by means of type PS-20 measuring test-bed, such as peanut pods was 10.30~14.39m/s, the immature peanut pods was 7.03~8.89m/s, the crushed stems was 4.51~5.46m/s, the peanut fruit stalk was 2.80~3.35m/s, and the peanut leaf was 1.74~2.13m/s; and the optimal parameters of cleaning device of peanut picker with air double-suction combined vibration screen, three parameters, including rotating speed of crank, height of air suction inlet, and rotating speed of fan, were selected as input variables. The loss rate and the impurity rate as output parameters and the performance test for the cleaning device were conducted. A quadratic orthogonal rotary regressive experimental design was employed to develop the second order polynomial regression models, which explained the relationship between the input and output parameters, and then, the main parameters of the cleaning device were optimized through Design-Expert 8.0.6 software. Experimental results indicated that the most optimum combination was that: the crank rotating speed of 200r/min, the air suction inlet height of 135mm and the fan rotating speed of 390r/min. The loss rate of peanut pods was 1.35% and the impurity rate was 1.75%.

Abstract:In order to solve the serious wear problem of D-knotter wiper inner cam, firstly, a new structure cam was designed. To be more precise, the original cylinder cam contour was replaced by using the offset arc surfaces of the cam theoretical surfaces, which means the point contact manner of convexity-convexity and convexity-plane was substituted by convexity-concave. Secondly, the surface equations of the improved cam were obtained, and then the pressure angle, initial contact area, initial maximum contact stress were calculated. Thirdly, the original and improved cams were manufactured by the turning and milling machine, which were using the aluminum alloy materials. Finally, a contrast experiment of wear pattern between the original and improved cams was designed, and the results were given by quantitative analysis. The results indicated that the improved cam mechanism reduced the pressure angle by an average of 25% than the original one in the majority of the rise travel. In contrast to the original one, the improved cam mechanism’s initial contact area can increase by approximately 50% and the initial maximum contact pressure decreased by 38%. After 10 hours’ runs of each cam mechanisms, the improved cam exceeds the original one by 31.7% in case of the width of the wear trace, and the abrasion value of improved cam is about 50% smaller than the original cam.

Abstract:The transport process of soil gas is pretty complex. It is influenced by many factors, which are influenced and restricted by each other. It has heavy spatial variation, and the spatial distribution and variation extent present very complex relationship with many factors. So it is very difficult to estimate the average conductivity of soil gas accurately in a large area when this happens in wild. This paper establishes a functional model about soil physical basic parameters and soil air permeability on the basis of data from measured soil samples. The results show that R2, the fitting degree of air permeability and water saturation, is up to 0.95 in sandy soil and more than 0.69 in clayed soil，because the clayed soil has higher soil structuralism. The fitting degrees of genetic algorithm system of the above two kinds of soil are more than 0.90. The absolutely relative error between the fitting air permeability and the measured air permeability is less than 0.1 by using this functional model. Furthermore, this functional model proves applicability and has good effect. The proposed method simplifies complicated calculation process of practical application and provides reference to gain soil gas transportation dynamics parameters quickly and easily.

Abstract:Un-deterministic dynamic of the energy process, water recycling and biological process in farmland is leading from its stochastic components, such as precipitation, evapotranspiration, heterogeneity of soil, topography and so on. The soil water balance is often described as a reservoir that is deterministically depleted via water losses due to evapotranspiration, runoff, leakage, and stochastically receives water from precipitation, so the stochastic property is the inherent nature of soil moisture. Based on the data of soil moisture, precipitation, meteorology and crop from 2000 to 2008 in Luancheng experimental station of agro-ecosystem of CAS on the stage of summer maize growth, the simulation was carried out with the stochastic model for soil moisture dynamics of the farmland at a point in piedmont plain of Taihang Mountain by using Laio model. The results show that the frequency and mean amount of daily rainfall from 2000 to 2008 in study area on the stage of summer maize growth are 0.2909, 10.71mm, respectively. And different changing trends were found among the frequency occurrence of different rainfall levels, the light rain and storm showed sharply increase trends, and the opposite trends was found in the moderate rain, for the heavy rain, the trends was slightly decrease. The revolution of soil water content of the growth stage of summer maize was expressed as increasing in June, stable in July, and decreased from August to September, and the maximum of soil water content was found in July, the value was 32.2%. A good agreement between the result of modeling and observation was found based on the curve shape of probability density function which included the curve peak value, the position of the peak, the confidence interval of 90% and the digital characteristic of the relative soil moisture which included the median value, expected value, and the variance(α=0.05). And the Laio model had a good application in the irrigated farmland, and the irrigation was treated as a rain. The amount of the irrigation which could made the soil moisture remained above 80% of field capacity on the stage of the summer maize growth under any loss in irrigation activity conditions was calculated by the Laio model, and the value was 32.1mm at the probability of 50%.

Abstract:In the Loess Plateau region, where climatic conditions are dry with severe water shortage, agricultural development is limited by water availability. Several studies have shown that due to high water consumption and poor land management, forest trees induce soil dry up and ecological degradation in Loess Plateau region. Pear jujube (Ziziphus jujuba Mill.) is one of the common tree species cultivated in this region due to its high drought tolerance and considerable economic benefits, but there are limited studies about its water consumptions. Sustainable cultivation of vast jujube plantations could prevent these ecological issues in the fragile ecological environment of Loess Plateau. Evapotranspiration (ET), which is the sum of plant transpiration and soil evaporation, is a continuous process of water loss in the soil plant atmosphere continuum. An accurate prediction of ET is necessary for developing agricultural management strategies to improve water use efficiency and ensure sustainable agricultural production. Therefore, the aim of this study on the simulation model of jujube ET would be significant. In addition, the single layer Penman-Monteith (PM) model is the most commonly used and the one recommended by FAO. However, the model is mostly used for dense canopy vegetation types as the “big leaf” assumption cannot sufficiently differentiate between vegtation and bare soil. As a measure of PM model weakness, Shuttleworth and Wallace developed a more complex two layer interactive model called the Shuttleworth-Wallace (SW) model that allows interaction between canopy and bare soil flue. The two layer SW model shows a superior performance over single layer models. In the Loess Plateau, due to water shortage, jujube forests are usually cultivated sparsely with low canopy cover, so it is necessary to select a suitable ET model for pear jujube forest. Based on the forest stand and climate condition, we parameterized the SW and PM models by using the data measured in 2012 and fulfilled the estimation of pear jujube forest ET in the fragile, semi arid, hilly Loess Plateau region of Mengcha Village in Shaanxi Province, China. Then the estimated ET by SW and PM models were validated and compared through ET computed by water balance theory, while the estimated transpiration by SW model was examined by observation from thermal dissipation probes (TDP) during 2013. The results showed that over the whole growing season, SW model performed better than PM model in ET estimation. Their accuracy was the poorest in the germination and leaf expansion stage and changed following the growth seasons. The accuracy of SW model in ET estimation met the evaluation criteria but PM model did not. The accuracy of SW model in transpiration estimation met the evaluation criteria, but it was affected by the weather condition, specifically, sunny days were better than rainy days. In the stand of sparsely cultivated jujube forest, the reliability of SW was comprehensively validated. Therefore, SW model could be the promising model applied in ET estimation to grasp the law of water consumption for jujube forest and similar stand in the semi arid Loess Plateau.

Abstract:The aim of this research is to realize the rapid measurement of soil available P content. The suitable proportion of available P could promote the crops grow. Taking ‘Lou’ soil as sample, the soil diffusion reflectance spectrum in 900~1700nm under different observation heights were collected by using the portable spectrographs. Firstly, five observation heights (5, 7, 10, 12, 15cm) were compared, and 10cm was considered to be the best. The abnormal samples were identified and eliminated by using 3 times standard deviation and principal component analysis method. That effectively improved the model precision. Then, the effect of four different wavelengths selecting methods (SPA, CARS, sCARS, RF) on modeling was analyzed. The result showed that sCARS was the best. Finally,the different nonlinear modeling methods (RBF neural network, WNN, LSSVM) were experimented. The results proved that LSSVM had the best result. When the observation height was 10cm, the modeling prediction correlation coefficient was 0.8581, and the prediction root mean square error was 10.8801. The results showed a high accuracy and feasibility of soil available P content prediction.

Abstract:It is easy to measure soil surface roughness by using a reference white board with a scale, from which the interface between soil and reference board can be detected and information of soil height can be read. Considering the low efficiency of manual reading, compute reading will be a good choice. But the impact of field illumination and weed interference makes compute reading susceptible. A soil roughness measuring method was proposed. In the proposed method, images were acquired with simplified reference scaling board. To process image automatically, color operation and threshold segmentation were used to decrease the effects of weeds and shadow, and then the soil boundary and scale were acquired, which would be used to measure the soil roughness. To improve the automaticity and robustness of the measuring method, chaotic particle swarm filter was applied for threshold segmentation. The test results showed that the soil roughness measurement method using color operation and chaotic particle swarm optimization reduced the requirement to image acquirement environment, and could calculate soil roughness quickly and efficiently, with the height error less than 0.5cm, the root mean square height error less than 5%, and the correlation length error less than 1%, which met the requirements of soil roughness real time on site measurement.

Abstract:Drought is one of the most important agricultural meteorological disasters in China, resulting in significant impacts on winter wheat growth and yield. Satellite remote sensing can provide real time and dynamic surface information and has become an effective tool for regional agricultural drought monitoring. In this study, the drought severity index (DSI) was first computed based on MODIS ET/PET and NDVI dataset from 2000 to 2012 for agricultural drought monitoring at prefecture-city level in winter wheat producing areas of both Shandong province and Henan province, and further evaluated the influence of agricultural drought on winter wheat yield during key phenological periods. The main conclusions from the study are as follows: the results from the Shandong province droughts occurring from September 2010 to February 2011 showed that DSI can not only monitor meteorological drought but can also reflect the spatial variations and temporal evolution for agricultural drought. Drought has varying impacts on winter wheat yield during different phenological stage of the growing season. Generally, the filling stage of winter wheat has the most important impact on winter wheat yield, during which drought induced soil water deficit affects the crops normal grouting intensity and results in reduction of winter wheat yield. The jointing stage follows and drought has negligible effect on winter wheat yield during the green up stage. The research can provide important reference for agricultural drought monitoring and drought impacts on crop yield in other agricultural regions.

Abstract:An annular optical-fiber-illuminating biofilm reactor (AOFBR) was developed with photosynthetic bacteria (PSB) attached on the surface of side-glowing optical fiber for the formation of biofilm and continuous photo-hydrogen production. To enhance mass transport and improve substrate bio-degradation efficiency within AFOBR, a two-dimensional mass transfer model was proposed based on the theory of mass transfer and kinetics of bio-chemical reaction. Results on numerical investigation revealed that characters of mass transfer obviously affected biodegradation within AFOBR. With the increase of inlet substrate concentration, substrate degradation efficiency was increased at early stage but decreased later. While, with the increase of flow rate, substrate bio-degradation efficiency was always decreased. The maximum substrate bio-degradation of 43.5% was available with 10g/L of inlet substrate concentration and 100mL/h of flow rate. To regulate mass transfer and maintain appropriate substrate concentration within biofilm was proved to be the effect way to achieve higher substrate degradation efficiency within the bioreactor.

Abstract:Normal maize starch and high-amylose maize starch were served as modal materials to prepare starch/polyvinyl alcohol (PVA) blends, respectively. The processes of anaerobic degradation were investigated in detail by evolutions of gas production, pH value in reactors, the potential of biogas-production, the energy conversion efficiency as well as the changes of film structures and compositions, to further understand the influence of the two native starches on biogas production. The results indicated that both of the films had good biodegradabilities in anaerobic condition and comparative potential of biogas-production. Nonetheless, the structure of high-amylose maize starch/PVA film was more suitable and beneficial to the anaerobic biodegradation than the normal maize starch/PVA film, because it could effectively avoid accumulation of volatile fatty acids, which contributed to the stable biogas production, 〖JP2〗short fermentation period, non souring in the reactor and higher energy conversion efficiency. Based on the agricultural film yield per year and biogas production of starch film, the corresponding energy production of high amylose maize starch/PVA film and normal maize starch/PVA film were 3.31×10 5GJ/a and 3.18×10 5GJ/a, respectively. It suggested that the starch film is a potential material for anaerobic digestion.

Abstract:To obtain real-time data during large-scale aerobic composting, realize automation control, optimize the composting process and improve product quality, a real-time monitoring system for temperature and oxygen concentration during large-scale aerobic composting with high integration and easy portability was developed on the basic of current studies. The system was consisted of temperature acquisition module, oxygen concentration acquisition module, signal processing module and data display and storage module. Performance experiments were operated in laboratory and actual large-scale aerobic composting, respectively. The results showed that the relative standard deviation (RSD) of temperature monitoring was inferior to 3.02% and response time was less than 45s; the RSD value and response time of oxygen concentration was inferior to 2.96% and 30s. In conclusion, the system has good performances such as high accuracy, good stability and fast response speed; it can satisfy the need of real-time monitoring of temperature and oxygen concentration in the process of large-scale aerobic composting and the need of scientific research.

Abstract:Quantitative characterization of particle morphology of manure is one of the key factors for modeling the fluid flow and degradation mechanism during manure management. This study applied three dispersion pretreatments (water dispersion, oven drying-mechanical vibration and vacuum freeze drying-mechanical vibration) and three analysis methods (scanning electron microscopy, dynamic image analysis and laser particle size analysis) to explore the particle size distribution and microscopic properties of pig manure. Scanning electron micrographs showed that manure particles had an irregular shape; the oven dried mechanically vibrated sample had more aggregates. The comparison between the results of different pretreatments indicated that the vacuum freeze drying-mechanical vibration could be selected as the preferred method because of the soluble components of manure and the aggregates generated during the oven drying process. There were differences in the values of characteristic parameters obtained by three analysis methods, and the dynamic image analysis was suggested as an effective method because of the direct measurement of particle morphology and the high degree of automation. Based on the optimized methods, the median diameter of manure particles was (501±16)μm, the span of particle size distribution was 1.45±0.04, and the shape factors including the aspect ratio and sphericity were 0.57±0.01 and 0.61±0.01, respectively.

Abstract:Straw and corn cob, taken as additional materials, were added into cattle manure to obtain mixture substrates of straw-cattle manure and corn cob-cattle manure, respectively. The mass percent for the main material of cattle manure was all set at 80% for two kinds of mixtures. And then the mixtures were aerobic composted to generate raw materials for compressing molding experiments. During the experiments, adding content of soil, moisture content of raw matters, and operating pressure and temperature were addressed. Experimental results indicated that adding soil into the mixture substrates could slightly increase the mechanical strength of the mixtures; the mechanical strength of the mixtures without adding soil was also very well, which was capable for planting operations. Moreover, regarding to the effect of the additional materials on the quality of the compressed substrates, the mechanical strengths for the two kinds of additional materials were almost equal. The density of the compressed substrate added straws was larger than that of the substrate added corn cobs, but the ability of absorbing and keeping water of the former was better than that of the latter. The suitable operating ranges for the moisture content of raw matters, and the pressure and temperature should be maintained at 10%~15%, 10~15kN and 80~120℃, respectively.

Abstract:Harvesting is one of the most critical processes in large scale microalgae culture， which occupies 20%~30% of total costs. As a flocculant, flocculation effect and kinetics of PAC were investigated on harvesting Chlorella sp., and the economic evaluation for harvesting microalgae was conducted. Different dosages of PAC were added into microalgae suspension, after stirring at 200r/min for 1min, the content of Chlorophyll was measured at different time. The results showed that five different dosages of PAC exhibited a high flocculation efficiency over 86% after 8min. The flocculation efficiency increased significantly (P<0.05) with increasing PAC dosage. The flocculation efficiency reached to 986% when the dosage of PAC was 123 5mg/L, and the residual aluminum concentration was 1328mg/kg in Chlorella sp. biomass. The flocculation mechanism of PAC was charge neutralization and sweeping flocculation, which acted in combination. And the cost was RMB￥266.04 when flocculating microalgae biomass was 1kg, which was 68.8% lower than the cost of RMB￥853.39 by centrifugation. The results of indicated that the flocculation of PAC obeyed the second order kinetics. Flocculation with PAC is feasible for harvesting microalgae.

Abstract:In order to solve the problem of accumulated heat and uneven condition of contact oxygen during straw fermentation process, the study of mixing motion of straw modeled by the discrete element method (DEM) was conducted. The accuracy of DEM models depends on the model parameters. Based on the image analysis, quantitative analysis of experiment and DEM method’s mixing state were conducted. A calibration process was developed to determine the parameter value by experiment of particle’s repose angle and motion. The research results showed that the size of subdomain was related to the particle’s size when using the image analysis of mixing characteristics. The size of subdomain affected the resolution of image analysis and it could be set as six times of particle’s diameter. The order of factors’ influence on the staw’s repose angle was the coefficient of static friction of particle/particle, the particle density, cohesion coefficient of particle/particle and coefficient of rolling friction of particle/particle. The order of factors’ influence on the mixing characteristics of the straw in rotary drum was the cohesion coefficient of particle/wall, the coefficient of rolling friction of particle/wall, coefficient of static friction of particle/wall, coefficient of restitution of particle/wall and coefficient of restitution of particle/particle. The orthogonal test results were compared with the experiment data. The granular material parameters could be used to describe the mixing characteristics of straw.

Abstract:With the development of computational fluid dynamics, the simulation accuracy and reliability are improved constantly. This technology is widely used in agricultural cold-chain logistics for the past few years which has significances to raise temperature homogeneity of the low-temperature environment, determine the goods stack, reasonably control refrigerating time, and improve the economic benefits of overall cold-chain logistics. This paper mainly described the pre-processing, computation and post-processing of computational fluid dynamics, reviewed the research advance of it in store, transportation and market process of agricultural cold-chain logistics, expounded the research methods and application characteristics of the technology, generalized and analyzed the advantages and deficiencies. Moreover, the paper also looked into the future trends of computational fluid dynamics in agricultural cold-chain logistics applications.

Abstract:Studying the features of gas changes in controlled atmosphere compartment contributes to improve performance and promote the application of controlled atmosphere compartment. In order to obtain the changing regulations of oxygen volume fraction in the controlled atmosphere compartment by liquid nitrogen injection, the air infiltration characteristics under thermal pressure of compartment were analyzed, and then the predicting model of oxygen volume fraction in the compartment was established. Moreover, verification experiment was also carried out. Results indicate that during the door-opening, the shorter the door-opening time is, the faster the average temperature rises. The relative humidity quickly rises to 100% within 60s after opening the door on condition that the relative humidity in the compartments is 90%~95%, and the average relative humidity is more than 97% during door-opening. What’s more, the rising velocity of oxygen volume fraction gradually decreases with longer duration of door-opening, and there is certain error between experimental value and theoretical value of oxygen volume fraction based on theoretical calculation and experiment. However, the relative error between the experimental and theoretical value is within 10% when the door-opening time is more than 3min. This research provides a reference for predicting matching amount for liquid nitrogen and safety range of oxygen volume fraction for safe operation.

Abstract:The aim of present work is to study the cross contamination and survival capacity of Aeromonas spp. on different food contacts in the kitchen. The recovery ratios of Aeromonas spp. using swabbing method from cutting boards and knives were firstly examined. Then, the survival of Aeromonas spp. on clean and contaminated cutting boards, stainless steel knives surfaces was studied. Based on the survival data and recovery ratios of Aeromonas spp., expected numbers of Aeromonas spp. on cutting boards and knives were calculated. Mathematical models describing survival of Aeromonas spp. as a function of time were also proposed. Meanwhile, in term of cutting boards as the cross contamination approach, combining survival model and further study were conducted to investigate the influence of the survival of Aeromonas spp. on the cross contamination level. Results indicated that the best fitting of recovery ratios of Aeromonas spp. from cutting boards and knives obtained by @Risk were Normal (0.66, 0.15) and Normal (0.72, 0.18), respectively. And Aeromonas spp. proved to survive longer on the contaminated cutting boards and knives than on the clean ones. Survival data for Aeromonas spp. could be well described by linear model (R2>0.88), and models without survival models included would overestimate the risk associated to bacterial transfer.

Abstract:To recognize early hidden bruises on kiwifruits, taking ‘Huayou’ kiwifruits as research object and near-infrared (NIR) hyperspectral imaging system as detection device, the NIR hyperspectral image of kiwifruits with no bruises and hidden bruises damaged in 3h were collected. The sample images were covered a wavelength of 900~1700nm. It was found that the no bruises and hidden bruises kiwifruits had obvious reflectance value between 900nm and 1350nm. Principal component analysis (PCA) was conducted on this spectral region, and it was found that 1050~1200nm was the optimal band for identifying kiwifruits with hidden bruises. Based on the weight coefficients of the principal component (PC) images in the optimal band and their correlation coefficients of reflection values between wavelengths, four characteristic wavelengths, i.e. 1057, 1090, 1120 and 1177nm, were extracted. After a secondary PCA, median filtering, threshold segmentation and mathematical morphology, recognition algorithm of kiwifruits with hidden bruises were proposed and then applied on 70 no bruises and 70 hidden bruises kiwifruits. Results showed that the correct identification rates for no bruises kiwifruits and hidden bruises kiwifruits reached to 100% and 95.7%, respectively. The average identification rate was 97.9%. This study indicates that NIR hyperspectral imaging technology is effective for identifying kiwifruits with early hidden bruises. Its results provide basic data for developing online detection system for bruised kiwifruits.

Abstract:In order to reduce storage losses, extend the storage period and improve the storage efficiency of winter jujubes, taking the winter jujubes in Zhanhua City as research object, a hyperspectral imaging system was built for detecting bruises happened less than 1h on ‘Zhanhua’ winter jujubes. The 256 hyperspectral images data within 871~1766nm wavelengths were obtained by the hyperspectral imaging system. The effective wavelengths were selected by using uninformative variables elimination (UVE) method and correlation coefficient method. Eventually, four characteristic wavelengths, 944, 1035, 1187 and 1376nm were selected. Four images were mapped to four characteristic wavelengths, the principal component analysis (PCA) was used based on the four images, and the first component of the image was selected to future process and segment. Many pretreatment methods were used for the first component of the image, such as gray level transformation and so on, and the method of adaptive threshold was applied to segment. Finally, the slightly damaged area could be obtained. Thus, the slight bruises on winter jujubes were recognized. Independent validation set of 100 bruised winter jujubes was used to evaluate the performance of the developed algorithm. Results showed that 98% of the bruised winter jujubes were recognized correctly.

Abstract:Pulsating fluidization has the advantages of high level contact of gas-solid and good mass and heat transfer. This paper presents the studies on two types of binary particles: identical sizes but different densities, and identical densities but different sizes. The experiments were carried out in a two dimensional fluidized bed which was made of plexiglas with the size of 200mm (length)×20mm (width) ×1000mm (height). Two air streams, steady flow and pulsating flow, were introduced into the fluidized bed to compare their effects on the mixing of particles. Experiments also investigated the mixing characteristics in different pulse intermittencies in terms of Ashton mixing index and the distribution of jetsam concentration. The results show that pulsating flows imposed on conventional fluidization can improve particle mixing at a lower average gas velocity. It is also found that the Ashton mixing index of equal densities binary mixtures is about 18% bigger than that of unequal densities binary mixtures. Thus the effect of density difference on particle mixing is more significant than the influence of size difference for binary particles.

Abstract:The microclimate environment monitoring is significant for agricultural production. Several characteristics of microclimate environment monitoring can be summarized from a variety of monitoring systems. Particularly, environmental data collected by multiple sensors have shown temporal and spatial properties simultaneously. The need for geospatial analysis and data visualization in monitoring microclimate environment became the main focus. In order to achieve this, a certain kinds of techniques were explored including internet of things (IOT) perception, the information fusion and data visualization. Furthermore, a unified interface specification was established to fuse IOT data with geographic information system seamlessly. In order to display and visualize the multidimensional environmental data, a series of visual methods were developed. Moreover, a web geographic information platform was built by using the Baidu Map APIs. In addition, several components were implemented including the geospatial analysis component, visual monitoring component, and some location based mobile applications. Finally, a flexible and vivid visualized monitoring system was formed. The adoption of this system could make it more convenient and easier to visualize and understand the microclimate environmental conditions via different terminal equipments.

Abstract:According to the monitoring and management needs of the modern greenhouse, a modern greenhouse intelligent monitoring system was designed based on the internet of things. The system was consisted of local monitoring subsystem, remote monitoring subsystem and database. The local monitoring subsystem was developed under the construction of Client/Server, but the remote monitoring subsystem with the construction of Browser/Server, and the database is the bridge between them. The hardware system based on distributed CAN bus was applied to realize the real time greenhouse environment data acquisition and equipment control. Also, the error data of the data acquisition system was on-line checked by distributing diagram. In order to improve the response and interactivity of the remote monitoring subsystem, the Ajax based Web data interactive way was applied. Combing the devices’ features, the temperature system intelligent control based on hybrid automata was applied to realize the automatic control of the greenhouse environment. The image recognition technology based on Zernike moments was applied to realize the automatic calibration. The infrared network camera was used to acquire the real-time images of the ventilation, and Zernike moments were utilized to extract the image features, identifying the current state of ventilation by comparing with the pre-set states of the system. Then the runtime could be calculated from the current state to full closed state of the ventilation. The tests showed that the system could provide stable data transmission and reliable control, satisfying the intelligent monitoring of the modern greenhouse.

Abstract:In order to solve fish classification and identification problems based on acoustic scattering data, a data fusion method based on SVM posterior probability was deduced, and a multi azimuth acoustic scattering data cooperative fusion fish classification method based on support vector machine (SVM) was proposed. Firstly, the wavelet packets coefficients singular value feature, temporal centroid feature and discrete cosine transform coefficients feature using multi azimuth acoustic scattering data were extracted, which reflected acoustic scattering characteristics of fish from different aspects. Secondly, the SVM classifiers made the decisions for features of each azimuth and the results were expressed in the form of posterior probability, each azimuth decision probability was used to weight the decisions of other azimuth simultaneously. Finally, the classification results were the ultimate output. Three kinds of fish were selected as the research objects and the classification accuracy (more than 92%) was presented based on the cooperative fusion method under the conditions of different numbers of azimuth. The processing results of experimental data indicated that the overall classification accuracy showed an increasing trend with the increase of number of azimuth. To examine the performance of classification further, large carp samples and small carp samples were used as training and testing samples mutually. The classification accuracy showed a increasing trend with the increase of number of azimuth in both cases, which reached more than 90% ultimately. The multi azimuth acoustic scattering data cooperative fusion method based on SVM can improve the correct classification ratios effectively.

Abstract:An equipment for aquaculture was developed which consisted of unmanned automatic cruise boat, environmental and ecological monitoring devices and remote service platform. It achieved a real-time online monitoring and precise control of field devices with high efficiency and low cost. By using the technology of automatic heading speed control, navigation and anti-collision, the unmanned boat realized the function of automatic cruise. Then, the boat carried a self made multi-functional device (one controller with different probes) to obtain ecological characteristics and various environmental parameters at each specified location, including water temperature, pH value, dissolved oxygen (DO), and oxidation-reduction potential (ORP). Detection parameters could be expanded according to the actual needs. The boat could obviously reduce the number of monitoring device and effectively improve its detection accuracy. Furthermore, information fusion, statistical analysis and configuration control were used to analyze the obtained data and precisely manage field aquaculture equipment. The result showed that the integrated monitoring equipment could meet the needs of large-scale and factory style aquaculture, and promoted the wider application of precision agriculture equipment in ordinary farmers.

Abstract:With the development of technology of internet of things (IOT), video data plays more and more important roles in monitoring of facility agriculture. Aiming at the video data requirement of identification for greenhouse vegetable diseases, this paper presents a monitoring video capture system orienting the identification of greenhouse vegetable diseases according to the characteristics of diseases of greenhouse leafy vegetables. The monitoring video capture system utilized the technology of IOT and the information acquired by sensors and monitoring cameras in greenhouse. The monitoring video capture system achieved the goal of intelligent greenhouse monitoring video acquisition by using a designed greenhouse video acquiring method. The greenhouse video acquiring method fused the case based reasoning and fuzzy reasoning, more specially, monitoring videos can be acquired through the greenhouse video acquiring method by matching the data collected by sensors in real time with the combination of environmental conditions in knowledge base. The fusion of case based reasoning and fuzzy reasoning can make up the incompleteness of the use with single method of case retrieval and ensure the accuracy of the data. The system also consisted of the functions of real time monitoring data and real time monitoring video. The results showed that the recall of the monitoring video capture system was 95.4%, which indicated that the monitoring video capture system can meet the video data requirement of identification for greenhouse vegetable diseases.

Abstract:In order to find the method of auto screening body temperature in pig’s cultivation, the thermal infrared imager was used to acquire the visible light image and infrared thermograph of pig at the same time from side-view. A series of registration and fusion processes were taken for the two kinds of images. A method which was based on improved active shape model (ASM) was proposed to detect the ear area of pig. Firstly, considering the characteristic of the pig ear profile, the marking rules of landmark points were restricted. Furthermore, the non subsampled contour transform (NSCT) coefficients of fusion image were substituted for the normalized first derivatives of profiles to build the gray level appearance model of each landmark. Finally, the process of average shape initialization was adapted based on matching skeleton endpoints. 50 images were tested by using the proposal method. The test result of overlap ratio greater than 0.8 accounted for 84%. The proposal method is significantly valuable on extracting the ear root area from recognized ear contour and developing the system of auto screening body temperature based on infrared thermograph.

Abstract:To achieve the pre-visual detection on potassium (K) stress，the microelectrode technique was used to measure the vacuolar membrane potential of cucumber leaves under four different levels of K-treatment. Kdeficiency made the vacuolar membrane potential of cucumber leaves more negative, whereas K-excess made the vacuolar membrane potential less negative. An obvious decrease of vacuolar membrane potential could be observed after 2d of severe K-deficiency plants. An obvious decrease of the vacuolar membrane potential could be observed after 4d of moderate K-deficiency plants. Conversely, an obvious increase of the vacuolar membrane potential could be observed after 2d of K-excess plants .The measurement of vacuolar membrane potential in cucumber leaf could be used for pre-visual detection of Kstress 10d before the appearance of visually morphological changes. All of these showed that the vacuolar membrane potential measurement may be used as an early diagnosing tool for K-stress in cucumber plants. It should be pointed out that the active transport of K+ does not contribute to the primary generation of membrane potential but is contingent upon an electrochemical proton gradient to furnish the required energy. Ultimately, the establishment of this gradient by the activity of the plasma membrane H+ pumping ATPase is the means by which plant cells become electrically polarized.

Abstract:To measure the parameters of soilless substrates quickly and accurately, based on a self-made compound sensor for multi-parameter of soilless substrates, combined with ZigBee wireless network technology, a portable wireless detector for multi-parameter of soilless substrates was designed. Considering the practicality and convenient operation, the principle of separated design was employed. The detector included a handheld terminal and a wireless compound sensor. The wireless compound sensor, including a self-made compound sensor and a CC2430 wireless module, collected data of water content, electrical conductivity and temperature in soilless substrates, and sent the data to the handheld terminal by wireless. Then, the handheld terminal received the data through another CC2430 wireless module, and progressed with a MSP430F5438A single chip. The measure results can be displayed, recorded, queried and deleted with the help of a 12864 LCD displayer and a keyboard. The tests demonstrated that error range of water content measurement was -0.4%~3.1%, and relative error range was -3.2%~9.6%; error range of electrical conductivity measurement was -0.015~0.179mS/cm, relative error range was -4.7%~10%; the error range of temperature measurement was -0.63~0.69℃, the relative error range was -1.1%~3.3%. The measurement error of detector was small enough to match the detection precision of agricultural production, and the detector was suitable for different substrates.

Abstract:The physiological role of plant, such as photosynthesis, is affected by water status. Water status of the plant can be reflected by leaf tensity. Foliar water potential and physiological capacitance has a coupling relationship with the cell sap concentration. Foliar physiological capacitance is associated with the effective thickness and area of leaf. The ratio of the area of leaf and effective thickness was defined as leaf tensity. According to this coupling relationship, the relational model of leaf tensity and water potential, physiological capacitance was derived. Leaves of Broussonetia papyrifera and Mulberry alba which grow in nature were selected as experiment materials. Physiological capacitance and water potential at different time were determined. Leaf tensity at different time was calculated by using the relational model. The result showed that there were differences between leaf tensity of Broussonetia papyrifera and Mulberry alba at different determination time. The correlation coefficient between photosynthetic parameters and leaf tensity of Broussonetia papyrifera was 0.933, physiological capacitance was 0.926 and water potential was 0.631, respectively. The correlation coefficient between photosynthetic indexes and leaf tensity of Mulberry alba was 0.843, physiological capacitance was 0.820 and water potential was 0.217, respectively. It demonstrated that the leaf tensity could better reflect the changes in water status of plant than physiological capacitance or water potential.

Abstract:Early detection of early blight on tomato leaves using NIR hyperspectral imaging technique based on modified gram schmidt (MGS) model and Bayesian logistic regression (BlogReg) were studied. Hyperspectral images of 70 infected and 80 healthy tomato leaves were acquired by hyperspectral imaging system in the spectral wavelength of 874~1734nm. Spectral reflectance of 30×30 pixels from region of interest (ROI) of hyperspectral image was extracted. Least squares-support vector machine (LS-SVM) model based on the full wavelength was established to detect early blight. Five (911nm, 1409nm, 1511nm, 1609nm, 1656nm) and nine wavelengths (901nm, 905nm, 908nm, 915nm, 918nm, 1123nm, 1305nm, 1460nm, 1680nm) were selected by MGS and BlogReg, respectively. Then, LS-SVM and linear discriminant analysis (LDA) models were built based on these effective wavelengths. Among these models, the correct classification rates were 93%~98% in calibration set and 96%~100% in prediction set, respectively. The result indicated that it was feasible to detect early blight on tomato leaves by using NIR hyperspectral imaging technique.

Abstract:This article chooses ten kinds of common trees in Beijing as the research objects. A 3D laser scanner was used to get the point cloud data of target trees. The tree crown volume was calculated by using the combined method of cubic lattice method and canopy surface triangulation. The tree factors from point cloud data and the calculated tree crown volume were analyzed to establish the estimation equations of tree crown volume, breast diameter, tree height, average crown height and average crown width. The accuracies of these equations were verified. Taking ginkgo as research object, the test results showed that the tree crown volume of ginkgo was significantly correlated to the breast diameter, tree height, average crown width and crown height. Finally, a three factor (breast diameter, average crown width, crown height) model was selected and verified on tree crown volume prediction of ginkgo. The results showed that the model had a good fitting accuracy of 90.5%. The three factor model was also employed on other species of trees and the results showed it could be used on the prediction of other tree crown volumes.

Abstract:Measurement of crop rooting system architecture and the calculation of root fractal dimensions plays an important role in precision crop rooting management. A technique for root visualization and analyzing was proposed to assess field state post-paddy wheat rooting system architecture. The proposed technique applied a root digitizer to measure wheat root system architecture, and changed the root system architecture into 3-D coordinates. The collected root topology data was then transferred to Pro/E platform for 3-D reconstruction. When the virtual root system was reconstructed, it was projected on three coordinate planes. The projected 2-D root architecture was then analyzed to derive fractal dimensions and fractal abundances. Results showed that the method could quantify the dynamics of the field-state wheat root system architecture. Both root fractal dimension and fractal abundance increased over time. Fractal dimension and fractal abundance in the top plane were always higher than that in the right plane. Starting from 98d after sowing, a rapid increase of fractal dimension and fractal abundance was observed in the front plane. Fractal dimension was, for all the three projections, strongly correlated to fractal abundance. Also, the fractal dimension and fractal abundance were both correlated to total root length.

Abstract:Due to the limit of heat transfer performance of building materials, the depth of the north wall affected by solar radiation was shallow in the passive solar greenhouse, which weakened the heat storage capacity of the wall interior. In this study, a phase change material wall with vertical air channels integrating solar concentrators was developed to fully strengthen the temperature and heat storage capacity of the wall interior by the active method and improve the temperature and heat storage capacity of PCM wallboards by the passive method. In order to prove the scientificity and feasibility of the identity, the experimental setup of multiple surfaces trough solar air collector and the experimental setup of phase change material wall with vertical air channels were built. And influencing characteristics of the air velocity in the collector and solar radiation on solar concentrators and influencing characteristics of the gap between air channels, the flow direction of heated air, and the velocity of the supply air on phase change material wall with vertical air channels were experimentally investigated, respectively. The results showed that the suitable air velocity in the collector was 1.4~1.8m/s, and the heat collection rose with the increase of solar radiation. The optimum conditions of phase change material wall were experimentally recommended: the gap was 400mm, the flow direction was downward, and the supply air velocity was 0.26m/s. While the experiment was carried out on the optimum conditions, the heat exchange effectiveness was 66.2%, and the active heat storage density was 9.43MJ/m3, 82.3% of which were stored in the block layer. Moreover, the discrepancy of the active heat storage and the heat release was 1.6%.

Abstract:In order to improve the ride comfort of a domestic self-dumping truck, a virtual prototype vehicle model was built through multi-body dynamics software Adams. And vehicle road test of ride comfort was implemented to verify the validity of this model. Taking the suspension stiffness and damp parameters of cab suspension as design variables, the root mean square (RMS) values of floor’s vertical and seat’s pitching weighted acceleration as optimization objectives, and the deflection of front and rear cab suspension as constraints, the Kriging approximation models were constructed based on optimal Latin hypercube design. On this basis, multi-objective optimization for self-dumping truck ride comfort was performed with particle swarm optimization algorithm, and the Pareto optimal set was obtained. Furthermore, a vehicle road test of ride comfort was conducted by using one of the optimal solutions. The results indicated that the Kriging approximation model with high fitting accuracy could significantly improve the efficiency of ride comfort optimization of self-dumping truck according to different weighting schemes of optimization objectives. The road test results showed that the overall weighted acceleration RMS values on the cab floor of the improved self-dumping truck were greatly reduced with a maximal reduction of 16.5%.

Abstract:Aiming at the problem that the convergence rate of identification algorithm in conventional adaptive controller is difficult to follow the model parameters actual change rate of semi-active air suspension, a damping multi-model adaptive control method, which could meet the high control quality requirement of semi-active air suspension with parameters changing in wide range, was proposed. In order to improve the system control speed, multiple fixed local linear models were established according to the actual damping control process of semi-active air suspension for different vehicle operating statuses and an adaptive model which initial value could be re-assigned was introduced to enhance the system control precision. The model switching control strategy based on minimum error was used to select the best matching model online and the optimum damping force was regulated by adaptive control method, thus constituting the damping multi-model adaptive control for semi-active air suspension. Simulation and vehicle road test results showed that the proposed method could improve the control quality of semi-active air suspension in wide range driving conditions effectively and the vehicle ride comfort was improved significantly.

Abstract:According to the problem of asynchronous motor speed control system, this paper proposes a cerebellar model aritculation controller coupled with active disturbance rejection controller (CMAC-ADRC) control algorithms based on adaptive parameter identification. The respective advantages of CMAC and ADRC were combined. And CMAC neural network was used for feedforward control. Its online learning was applied which suppressed overshoot system, enhanced the robustness and dynamic performance of the system. ADRC was used for feedback control which further enhanced the anti jamming capability. The inertia was identified by using model reference adaptive parameter identification technique and ADRC compensation factors were optimized. Taking converter and asynchronous motor as control objects, the simulation was carried out. The simulation results showed that the response amplitude caused by disturbance of control system using CMAC-ADRC based on adaptive identification was 44.57% of the one using first-order optimization ADRC, and 17.69% of the one using CMAC-PD. Meanwhile, the recovery time of disturbance was 50% of the one using first-order optimization ADRC, and 60% of the one using CMAC-PD. Some experiments were finished on the experiment platform based on MCU-CPLD-DSP. The experiment result showed that with CMAC-ADRC, the overshoot, rising time, response amplitude caused by disturbance, and recovery time of disturbance were 45.49%, 53.33%, 71% and 76.47% of the one using first-order optimization ADRC, respectively.

Abstract:The 3-RRR+(S-P) spherical parallel mechanism is very similar to human shoulder and hip joint. This mechanism can be taken as the prototype of the shoulder and hip joint for humanoid robot. However, the secure workspace of 3-RRR+(S-P) spherical parallel mechanism is so small, that could not meet the requirements of the shoulder and hip joint for humanoid robot. According to bionics and structure of human thighbone, the design idea of biasing output was proposed. And then, the 3-RRR+(S-P) bionic joint mechanism with biasing output was proposed based on the 3-RRR+(S-P) spherical parallel mechanism. For the bionic joint mechanism and prototype mechanism, there was a certain mapping relation between their secure workspaces. The mapping relation was obtained based on conversion of coordinates, and then, the secure workspace of the proposed bionic joint mechanism was obtained. The 3-RRR+(S-P) bionic joint mechanism with biasing output retained the kinematic and mechanical performance of prototype mechanism, and had a substantially increased secure workspace. The secure workspace of the proposed bionic joint mechanism could meet the requirements of the shoulder and hip joint for humanoid robot absolutely.

Abstract:Aiming at the errors of compliant parallel robot, a study on the motion planning and trajectory tracking of robot system was presented to improve the overall performance. According to the performance requirements, the structural parameters of compliant joint were designed. The characteristics of compliant joint were analyzed. The analysis model and the kinematic equation were obtained. Aiming at the length errors of links made by axis drift, a numerial method for determining the actual length of drive and driven links was proposed. Based on the radial basis function (RBF) neural network, a model approximation control method was designed to compensate the vibration and the parameter perturbation errors of parallel robot system for tracking the desired trajectory. The virtual simulation model of compliant joint parallel robot system was estalished by SolidWorks, ANSYS, ADAMS and Matlab/Simulink. The simulation results show that the errors of end-effector trajectory without compensation of compliant joint errors can be reduced by 84% based on the proposed motion planning and control method, which is effective to improve the operating accuracy of compliant joint parallel robot system.