拖拉机功率与深松作业效率关系研究
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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 k W、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。
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.
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.
引文
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[17]李健敏,赵庚星,李涛,等.山东省小麦施肥特征与评价[J].中国农业科学,2018,51(12):2322-2335.
[18]王玲,王新,刘健,等.基于虚拟仪器的柔性化农机机群远程监测系统研究[J].农业机械学报,2014,45(1):34-39.WANG Ling,WANG Xin,LIU Jian,et al.Research on flexible remote monitoring system of agricultural machinery based on virtual instrument[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(1):34-39.(in Chinese)
[19]吴才聪,蔡亚平,罗梦佳,等.基于时间窗的农机资源时空调度模型[J].农业机械学报,2013,44(5):237-241,231.WU Caicong,CAI Yaping,LUO Mengjia,et al.Time-windows based temporal and spatial scheduling model for agricultural machinery resources[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(5):237-241,231.(in Chinese)
[20]赵世卿,吴永峰,李光林,等.丘陵山区农机深松作业深度和面积远程监测系统[J].西南大学学报(自然科学版),2018,40(12):22-29.ZHAO Shiqing,WU Yongfeng,LI Guanglin,et al.A remote monitoring system for depth and area of agricultural machinery subsoiling in hilly regions[J].Journal of Southwest University(Natural Science Edition),2018,40(12):22-29.(in Chinese)
[2]史国滨,王熙.基于ASP.NET的农机监控Web GIS系统性能优化[J].安徽农业科学,2011,39(5):2821-2823.SHI Guobin,WANG Xi.Optimization of performance of agricultural machinery monitoring Web GIS system based on ASP.NET[J].Journal of Anhui Agricultural Science,2011,39(5):2821-2823.(in Chinese)
[3]刘阳春,苑严伟,张俊宁,等.深松作业远程管理系统设计与试验[J].农业机械学报,2016,47(增刊):43-48.LIU Yangchun,YUAN Yanwei,ZHANG Junning,et al.Design and experiment of remote management system for subsoiler[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(Supp.):43-48.(in Chinese)
[4]孟志军,尹彦鑫,罗长海,等.农机深松作业远程监测系统设计与实现[J].农业工程技术,2018,38(18):34-37.
[5]刘卉,孟志军,王培,等.基于农机空间轨迹的作业面积的缓冲区算法[J].农业工程学报,2015,31(7):180-184.LIU Hui,MENG Zhijun,WANG Pei,et al.Buffer algorithms for operation area measurement based on global navigation satellite system trajectories of agricultural machinery[J].Transactions of the CSAE,2015,31(7):180-184.(in Chinese)
[6]王培,孟志军,尹彦鑫,等.基于农机空间运行轨迹的作业状态自动识别试验[J].农业工程学报,2015,31(3):56-61.WANG Pei,MENG Zhijun,YIN Yanxin,et al.Automatic recognition algorithm of field operation status based on spatial track of agricultural machinery and corresponding experiment[J].Transactions of the CSAE,2015,31(3):56-61.(in Chinese)
[7]CAI Y,WU C,LUO M,et al.Automatic recognition method of operation status for agricultural machinery based on GNSS data mining[C]∥China Satellite Navigation Conference(CSNC)2012 Proceedings,2012:135-145.
[8]HUANG P,LUO X,ZHANG Z.Headland turning control method simulation of autonomous agricultural machine based on improved pure pursuit model[C]∥IFIP International Federation for Information Processing 2010,2010:176-184.
[9]ZHOU K,LECK J A,SRENSEN C G,et al.Agricultural operations planning in fields with multiple obstacle areas[J].Computers and Electronics in Agriculture,2014,109:12-22.
[10]HAMEED I A,BOCHTIS D D,SRENSEN C G,et al.Automated generation of guidance lines for operational field planning[J].Biosystems Engineering,2010,107(4):294-306.
[11]PALMER R J,WILD D,RUNTZ K.Improving the efficiency of field operations[J].Biosystems Engineering,2003,84(3):283-288.
[12]BOCHTIS D D,VOUGIOUKAS S G.Minimising the non-working distance travelled by machines operating in a headland field pattern[J].Biosystems Engineering,2008,101(1):1-12.
[13]BOCHTIS D D,SRENSEN C G.The vehicle routing problem in field logistics part I[J].Biosystems Engineering,2009,104(4):447-457.
[14]张燕,徐华君.中国农业机械动力空间格局分析[J].农机化研究,2015,37(11):12-16.
[15]袁伟.上海崇明地区农机动力与农机具配套发展策略[J].南方农机,2016,47(5):23-28.
[16]尹彦鑫,王成,孟志军,等.悬挂式深松机耕整地耕深检测方法研究[J].农业机械学报,2018,49(4):68-74.YIN Yanxin,WANG Cheng,MENG Zhijun,et al.Operation quality measurement method for tilling depth of suspended subsoiler[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(4):68-74.(in Chinese)
[17]李健敏,赵庚星,李涛,等.山东省小麦施肥特征与评价[J].中国农业科学,2018,51(12):2322-2335.
[18]王玲,王新,刘健,等.基于虚拟仪器的柔性化农机机群远程监测系统研究[J].农业机械学报,2014,45(1):34-39.WANG Ling,WANG Xin,LIU Jian,et al.Research on flexible remote monitoring system of agricultural machinery based on virtual instrument[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(1):34-39.(in Chinese)
[19]吴才聪,蔡亚平,罗梦佳,等.基于时间窗的农机资源时空调度模型[J].农业机械学报,2013,44(5):237-241,231.WU Caicong,CAI Yaping,LUO Mengjia,et al.Time-windows based temporal and spatial scheduling model for agricultural machinery resources[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(5):237-241,231.(in Chinese)
[20]赵世卿,吴永峰,李光林,等.丘陵山区农机深松作业深度和面积远程监测系统[J].西南大学学报(自然科学版),2018,40(12):22-29.ZHAO Shiqing,WU Yongfeng,LI Guanglin,et al.A remote monitoring system for depth and area of agricultural machinery subsoiling in hilly regions[J].Journal of Southwest University(Natural Science Edition),2018,40(12):22-29.(in Chinese)