基于AUKF的刮板输送机直线度检测技术研究

Research on Straightness Detection Technology of Scraper Conveyor Based on AUKF

针对刮板输送机直线度检测技术在使用中稳定性差、精度较低问题,提出了自适应无迹卡尔曼滤波(AUKF)算法。首先理论分析得到误差模型,结合实际作业情况,利用惯导、忽略杆臂误差的AUKF和补偿杆臂误差的AUKF进行了轨迹解算。实验结果显示,带有杆臂误差补偿的方法提升稳定性27.8%,提升精度60.5%。

An adaptive unscented Kalman filter(AUKF)algorithm is proposed to address the issues of poor stability and low accuracy in the straightness detection technology of scraper conveyors.Firstly,an error model is derived through theoretical analysis.Combining with the actual operational conditions,trajectory computation is performed using AUKF with inertial navigation,AUKF that ignores boom arm errors,and AUKF that compensates for boom arm errors.The experimental results demonstrate that the method with boom arm error compensation improves stability by 27.8%and accuracy by 60.5%.