王培,孟志军,安晓飞,陈竞平,李立伟.拖拉机功率与深松作业效率关系研究[J].农业机械学报,2019,50(Supp):87-90.
WANG Pei,MENG Zhijun,AN Xiaofei,CHEN Jingping,LI Liwei.Relationship between Agricultural Machinery Power and Agricultural Machinery Subsoiling Operation[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(Supp):87-90.
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拖拉机功率与深松作业效率关系研究   [下载全文]
Relationship between Agricultural Machinery Power and Agricultural Machinery Subsoiling Operation   [Download Pdf][in English]
投稿时间:2019-04-20  
DOI:10.6041/j.issn.1000-1298.2019.S0.014
中文关键词:  拖拉机  农机功率  深松作业  作业效率
基金项目:国家重点研发计划项目(2016YFD0700300-2016YFD0700303、2017YFD0700604)
作者单位
王培 北京农业智能装备技术研究中心
国家农业信息化工程技术研究中心 
孟志军 北京农业智能装备技术研究中心 
安晓飞 北京农业智能装备技术研究中心
国家农业信息化工程技术研究中心 
陈竞平 北京农业智能装备技术研究中心 
李立伟 北京农业智能装备技术研究中心 
中文摘要:为了研究农机实际作业过程中的农机功率与深松作业效率之间的关系,以山东省深松作业为研究对象,选取323台福田雷沃重工生产、功率范围为52.20~197.61kW、装载农机深松作业远程监测终端的拖拉机,采集2015年4月到2017年4月之间深松作业运行轨迹数据37 981条,计算深松作业面积、作业时间和效率。将数据集按照无放回抽样方法分为建模集(80%)和验证集(20%),通过线性回归分析,建立了基于拖拉机功率的深松作业效率模型,拖拉机功率与深松作业效率有明显的线性关系,其R2达到0.9147,均方根误差为0.1684hm2/h,模型验证结果均方根误差为0.3396hm2/h。拖拉机作业效率模型可为拖拉机服务组织在拖拉机作业时间窗口条件下进行拖拉机作业的合理调度与分配提供科学依据。
WANG Pei, MENG Zhijun, AN Xiaofei, CHEN Jingping and LI Liwei
Beijing Research Center of Intelligent Equipment for Agriculturel;National Engineering Research Center for Information Technology in Agriculture,Beijing Research Center of Intelligent Equipment for Agriculture,Beijing Research Center of Intelligent Equipment for Agriculture;National Engineering Research Center for Information Technology in Agriculture,Beijing Research Center of Intelligent Equipment for Agriculture and Beijing Research Center of Intelligent Equipment for Agriculture
Key Words:tractors  agricultural machinery power  subsoiling operation  operation efficiency
Abstract:With the development of informatization, China has promoted “Internet+agricultural machinery operation”, which accelerated the promotion of agricultural machinery operation monitoring and the agricultural machinery monitoring & scheduling platform, and improved the quality and efficiency of agricultural machinery operation. Massive data of agricultural machinery operation was accumulated at the same time. In order to research on the relationship between the power of agricultural machinery and agricultural machinery in the process of subsoiling efficiency, the subsoiling operation data in Shandong Province was taken as the research object. In the research, totally 323 tractors installed subsoiling agricultural machinery remote intelligent monitoring terminal were selected as analysis samples (produced by Foton Lovol Corporation). The experiment data included 37981 sets about the operation area, duration of the operation and efficiency of agricultural machinery operation from April 2015 to April 2017. The agricultural machinery power range was from 52.20kW to 197.61kW. All the experiment data were divided into two parts: calibration set (80%) and validation set (20%) by sampling without replacement method. The agricultural machinery subsoiling efficiency model was established based on agricultural machinery power. The correlation coefficient between agricultural machinery power and subsoiling operation efficiency was 0.9147, and RMSE was 0.1684hm2/h. The RMSE of validation set was 0.3396hm2/h. The agricultural machinery subsoiling efficiency model provided a new method for agricultural machinery service organization to allocate agricultural machinery and assign tasks reasonably.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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