基于四元数误差状态卡尔曼的杆塔监测系统

为了减少因杆塔倾斜造成的电力事故,该文设计了用于野外杆塔的姿态监测系统。系统主要采用误差状态卡尔曼(ESKF)算法对原始信号进行滤波处理,再通过欧拉角和四元数变换的方法进行姿态解算。通过在每次迭代中产生新的对应特征来递归地校正估计的状态,并保持系统在计算上满足四元数的约束,实现陀螺仪和加速度计的随机误差补偿滤波。处理后的数据经过无线传输模块传至后台服务器,最终实现远程监控。通过实验室验证与实地测试一段时间后,结果表明,系统功能稳定,精度高,满足了杆塔的倾斜检测。

Tower Monitoring System Based on Quaternion Error State Kalman

In order to reduce the power accidents caused by tower tilt, an attitude monitoring system for the poles and towers in the field is designed in this paper. The system mainly uses the error state Kalman(ESKF) algorithm to filter the original signals, and then calculates the attitude through the method of Euler angle and quaternion transformation. By generating new corresponding features in each iteration to recursively correct the estimated state, and keeping the system meet the quaternion constraint in calculation, the random error compensation filtering of gyroscope and accelerometer is realized. The processed data is transmitted to the background server through the wireless transmission module, and finally the remote monitoring is realized. After a period of laboratory verification and field test, the results show that the system has stable function and high precision, and meets the tilt detection of the tower.