Method and System of Plowing Depth Online Sensing for Reversible Plough. Issue 17 (2018)

• Record Type: Journal Article
• Authors: Yin, Yanxin; Guo, Shuxia; Meng, Zhijun; Qin, Wuchang; Li, Bin; Luo, Changhai
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 17(2018)
• Page Start: 326
• Page End: 331
• Publication Date: 2018
• Subjects: reversible plough -- plowing depth -- online sensing -- GPS -- embedded system -- working quality; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.08.199
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The reversible plough is a quite useful farm machinery for deep tillage, which is directly mounted to the tractor. It works on both the left and right side with bilateral turnover mechanism and automatically reverses the position. According to its structure characteristic, based on deviation correction method, a depth online sensing model was proposed firstly by integrated attitude data from tractor and reversible plough. In this model, plowing depth was obtained by calculate the pitch attitude of the lower link which suspended at the back part of a tractor and reversible plough. Then, on the basis of this model, developed ARM embedded microprocessor based plowing depth detection sensors and deep plough online sensing system. This system which integrated the Global Positioning System(GPS), the General Packet Radio Service (GPRS) and SD Card, was designed for real-time collecting the operation information from tractor and reversible plough, such as deep plough, position, velocity and heading. In the meanwhile, all the collected information stored in terminal device of this system and simultaneously transmitted to remote data center for further fusion data processing and comprehensive evaluation of operation quality. This calibration tests result conformed that the system calibration absolute error was -3.61mm, which indicated the system had high accuracy in static condition. The field experiments result showed that maximum absolute error was 15.76mm, the maximum relative error was 8.46%, RMSE was less than 12.07mm, and the maximum coefficient of variation was 0.06. Result showed that this developed plowing depth online sensing system has a high measuring accuracy and reliable performance. It is worthwhile to spread its application.