农机具姿态倾角测量系统设计与试验

农机具姿态倾角测量技术是实现农机装备精准作业的关键技术之一。为进一步提高农机装备作业质量,以ADIS16445微惯性MEMS传感器和STM32F446核心处理器搭建硬件平台,以欧拉角法解算姿态,建立卡尔曼滤波模型融合加速度计与陀螺仪信息,实现农机具姿态倾角的精准测量。融合算法模型考虑陀螺仪零偏特性,并根据MEMS微传感器运动特性,自适应模型误差协方差矩阵Q与R,适应不同工况下农机具姿态倾角测量。采用SGT320E三轴多功能转台与BD982双天线定位测姿模块对系统进行测试与验证。三轴多功能转台试验结果表明,ADIS16445内置陀螺仪与加速度计性能合格,满足系统设计硬件要求;卡尔曼滤波融合模型精准有效,倾角静态测量误差精度为0.15°,动态测量精度典型值为0.3°,最大测量误差为0.5°。田间作业试验结果表明,自适应模型能保证农机具姿态倾角测量系统在不同工况下的测量精度,更稳定可靠,测量平均误差为0.55°。该文研究的农机具姿态倾角测量系统可满足农机装备精准作业要求。

Design and test of tilt angle measurement system for agricultural implements

Abstract: Agricultural implements tilt angle measurement is one of the key technologies to achieve agricultural machinery and equipment precision operations. For example, the precision navigation control and the leveling control of agricultural machinery are all dependent on the accurate measurement of tilt angle. What''s more, agricultural implements of tilt angle are one of the key parameters of agricultural mechanics modeling and agricultural machinery safety warning learning. In order to further improve the quality of agricultural machinery operation, we developed a new agricultural implement tilt angle measurement system in this paper and verified by tests on three _axis turntable platform and field. Modern micro-electromechanical systems (MEMS) technologies provide the moderate-cost and miniaturized solutions for the development of attitude reference system. Using highly-integrated inertial measurement units (IMUs) ADIS16445 provided by ADI company and micro ARM processor STM32F446 provided by ST company, we built the hardware platform. ADIS16445 iSensor(r) includes tri-axial gyroscopes and tri-axial accelerometers, the raw sensors data was sampled by STM32F446RC processor through SPI interface. The attitude calculation was carried out based on the Euler angle algorithm. The Kalman filter model with four state vectors and two observations was established to fuse the accelerometer and gyroscope information to achieve the accurate measurement of the tilt angle of agricultural machinery. Considering the zero bias and drift characteristics of the gyroscope and the motion characteristics of the MEMS micro sensor, adaptive error covariance matrix Q and R rules were established to achieve precise tilt angle measurement of agricultural implements under different working conditions. Tests were conducted on SGT320E triaxial turntable platform and ZP9500 high level sprayer provided by LOVOL company dual in the field with the assistance of antenna positioning and attitude module BD982 provided by Trimble company. The SGT320E triaxial turntable platform was the standard equipment for testing the angular motion parameters and inertial systems. By setting the triaxial motion parameters to simulate a variety of motion states, it had speed, position and sine swing modes on all triaxial with a rate resolution of 0.0001°/s. In this paper, we used six position accelerometer calibration method and gyroscope error model to verify the performance of accelerometers and gyroscopes. Three-axis multi-function turntable test results showed that ADIS16445 built-in gyroscopes'' and accelerometers'' zero bias were under 0.15°/s and 0.075 mg, qualified to meet the system design hardware requirements. Kalman fusion algorithm were more accuracy and effective compare to simple integral by gyroscope and can solve the problem of zero bias and drift characteristics of the gyroscope with tilt static measurement error accuracy was 0.15°, typical dynamic measurement accuracy was 0.3°, maximum measurement error was less than 0.5°. The BD982 supports high precision positioning, attitude and heading output with high stability and fast dynamic response, which is widely used in construction machinery, automobiles, agricultural machinery and other fields, making it to be the leader of the industry. In this paper, the baseline length was 1.4 m with the measurement accuracy of 0.1°. Test results from high level sprayer showed that the average error of the attitude inclination was less than 0.55°, maximum measurement error was less than 0.91°, which satisfied the precise operation requirement of the agricultural equipment. Test results also verified that self-adaptive Kalman filter algorithm was more accuracy and stable than normal Kalman filter algorithm, which made the system development by this paper have more applicability. The agricultural implements tilt angle measurement system developed in this paper not only can reducing costs but also can improving the quality of agricultural machinery operations.