田间作业车辆外部加速度辨识与姿态测量系统研制

复杂田间作业环境与精细作业效果要求农机装备具备实时精准感知农机具姿态的能力,田间作业时普遍存在的车辆外部加速度对此带来挑战。为进一步提高农机装备作业质量,该文以6轴微惯性传感器为硬件传感器,以方向余弦矩阵法进行姿态解算,基于一阶外部加速度模型设计卡尔曼滤波融合算法,实现动态情况下田间作业车辆外部加速度辨识与姿态精准估计。分别采用Innova 2100型摇床与装配有MTi300航向姿态参考模块的高地隙喷雾机对系统进行试验验证。摇床试验结果表明:在外部加速度小于10g情况下,系统对外部加速度辨识误差小于0.214 m/s2;田间作业高地隙喷雾机试验结果表明,相比于MTi300,横滚角最大误差为0.23?,俯仰角最大误差为0.39?。说明该文研制姿态测量系统可准确辨识外部加速度与测量姿态,研究结果可为满足精细农业作业要求的姿态测量系统研发提供依据。

Development of external acceleration identification and attitude estimation system of field working vehicle

Abstract: The development of precision agriculture, intelligent agricultural machinery and equipment are an effective way to alleviate the current tense situation in world food security. The complex field environment and meticulous work effects require the agricultural machinery to have the ability to perceive the attitude of the agricultural machinery accurately in real time. For example, the precision navigation control and the leveling control of agricultural implements are all dependent on the accurate measurement of attitude. What''s more, the attitude of agricultural implements is one of the key parameters of agricultural mechanics modeling and agricultural implements safety warning learning. However, the external acceleration of the vehicle, which is generally present under dynamic operation conditions, poses a challenge. In order to further improve the precision operation of agricultural machinery and equipment, the paper developed a minimal hardware system for external acceleration identification and attitude estimation used for field working vehicles, and verified by the experiments taken place on the Innova 2100 shaker and the ZP9500 high level sprayer in the field. Modern micro-electromechanical systems (MEMS) technologies provide the moderate-cost and miniaturized solutions for the development of attitude reference system. By using of highly-integrated inertial measurement units (IMUs) ADIS16445 provided by ADI company and micro ARM processor STM32F446 provided by ST company, the hardware platform was built. ADIS16445 ISensor(r) included 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 direction cosine matrix algorithm. Based on the gyroscope and accelerometer measurement model, an one order external acceleration measurement model was proposed, and a Kalman filter fusion algorithm with 4 state vectors was established. Since the bias of gyroscopes and accelerometers was stable after hardware preheated, the impact of bias of MEMS inertial sensors in the fusion algorithm was not considered. Innova 2100 shaker is a standard equipment of rotary motion, by setting different rotation speed, different centripetal accelerations can be achieved to verify the external acceleration identification. Innova 2100 shaker test results showed that the measure error was less than 0.214 m/s2 under the external acceleration lower than 10g. Field experiments were conducted on Innova 2100 shaker and the ZP9500 high level sprayer provided by LOVOL company with the assistance of attitude and position reference system (AHRS) MTi300 provided by Xsens company. The MTi300 AHRS provide high precision attitude and heading output with high stability and fast dynamic response with dynamic measurement accuracy of 0.3 °, which make it widely used in navigation implements, automobiles, agricultural implements and other fields. Experiment results from high level sprayer showed that compared to the MTi300 AHRS, the average measurement error of roll angle was 0.069 ° and the maximal measurement error was 0.23 ° respectively. The average measurement error of pitch angle was 0.078 ° and the maximal measurement error was 0.39 ° respectively. Test results verified that the proposed Kalman filter algorithm was accuracy and stable, which can improving the quality of agricultural implements operations and have more applicability.