基于IMMUKF的冲量式测产系统研究

doi:10.13733/j.jcam.issn.20955553.2021.12.21

摘要/Abstract

摘要： 为适应精准农业的发展趋势，提高测产计量系统的精度，开发一套基于IMMUKF算法的冲量式测产系统。该系统由冲量传感器模块、北斗定位模块、DTU传输模块和上位机等组成。系统通过传感器模块进行信号的采集和处理，采用CAN通信方式将处理后的数据发送至上位机。上位机使用IMMUKF滤波算法对传感器上传的数据进行滤波，最终根据标定曲线得到谷物产量。通过车辆空载试验，采用IMMUKF算法与KF和UKF算法进行对比验证，结果表明IMMUKF算法的滤波效果更好，均方差为0.000 42 N。通过传感器标定试验，确定传感器的检测值与实际谷物重量的关系。通过大田测产试验，得出每个地块的产量分布图，试验结果表明该测产系统的平均误差达到3.911%。

关键词: 精准农业, 冲量式测产系统, IMMUKF算法, 谷物重量, 产量分布

Abstract: In order to adapt to the development trend of precision agriculture and improve the accuracy of the yield measurement system, a set of impulse yield measurement systems was developed. The impulse sensor module, Beidou module, DTU transmission module, and upper computer were included in the system. The information of the impulse sensor was collected and sent to the upper computer through CAN communication. On the upper computer, the yield data was filtered by the IMMUKF algorithm, and then the grain yield was obtained according to the calibration curve. Through the vehicle noload test, IMMUKF algorithm, KF, and UKF algorithm were used for comparison and verification. The results showed that the IMMUKF algorithm has a better filtering effect, and the mean square deviation is 0.000 42 N. Through the calibration test of the sensor, the relationship between the detection value of the sensor and the actual grain weight was determined. After the field yield test, the yield map of each field was made. The test results show that the average error of the yield measurement system was 3.911%.

Key words: precision agriculture, impulse production measurement system, IMMUKF filtering algorithm, grain weight, yield map

中图分类号:

S225.93

赵博, 赵士猛, 安飒, 刘阳春, 汪凤珠, 邢高勇. 基于IMMUKF的冲量式测产系统研究[J]. 中国农机化学报, 2021, 42(12): 144-149.

Zhao Bo, Zhao Shimeng, An Sa, Liu Yangchun, Wang Fengzhu, Xing Gaoyong. . Study of production measurement system based on IMMUKF[J]. Journal of Chinese Agricultural Mechanization, 2021, 42(12): 144-149.

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