农业机械学报2024，Vol.55Issue(9)：52-64,13.DOI:10.6041/j.issn.1000-1298.2024.09.004
基于多传感器数据融合的旋耕耕深检测系统研究
Rotary Tillage Depth Detection Based on Multi-sensor Data Fusion
摘要
Abstract
Tillage depth is usually used to measure the quality of rotary tillage.Suitable tillage depth can break soil compaction,improve soil structure and promote crop root growth.At present,the research scene of ploughing depth detection is mainly dry field,and the detection method is mainly indirect detection by inclination sensor.However,the soil of paddy field is soft,and the problems of sinking and attitude change will occur in the operation process.Therefore,a tillage depth detection system suitable for different soil environments was designed.In order to detect terrain relief and tool sag,a ground copying mechanism was designed,and its design parameters were explored through coupling simulation to verify its feasibility.In order to improve the indirect detection stability of single sensor,the detection method of three-point suspension inclination detection and relative elevation data fusion of Beidou system(BDS)were used,and a tillage detection model(TDM)was established.Adaptive iterative extended Kalman filter(AIEKF)was proposed to filter and then fuse data acquired by sensors to obtain more stable and accurate depth.On the basis of referring to the traditional tillage depth measurement method,the RTK-BDS elevation difference measurement method was proposed to obtain the true tillage depth value,and compared with the traditional method.The coupling simulation results showed that the absolute error was less than 0.5 cm and the maximum shape variable of soil trough elevation was 2.89 mm.Field experiment results showed that TDM detection model can effectively reflect the change of ploughing depth.The signal-to-noise ratio of AIEKF processing data was increased by 1.41 dB on average compared with that of KF processing data,and the ploughing depth data obtained by fusion was increased by 2.30％and 2.07％on average compared with the ploughing depth MAPE detected by two single sensors,respectively.After fusion,the average MAPE was 3.95％and the average RMSE was 1.08 cm.The maximum absolute error of RTK-BDS difference truth detection method and traditional detection method was 2.45 cm,which can complete the truth detection of ploughing depth well.关键词
旋耕整地/运动仿真/耕深检测/RTK-BDSKey words
rotary tillage preparation/motion simulation/tillage depth detection/RTK-BDS分类
农业科技引用本文复制引用
马若飞,伟利国,赵博,周利明,刘阳春,邢高勇..基于多传感器数据融合的旋耕耕深检测系统研究[J].农业机械学报,2024,55(9):52-64,13.基金项目
国家重点研发计划项目(2021YFD2000601) （2021YFD2000601）
