多传感器电流测量系统信号处理算法研究

INVESTIGATION ON THE SIGNAL PROCESSING ALGORITHMS APPLIED IN THE MULTI-SENSOR SYSTEM MEASURING ELECTRIC CURRENT

通过磁传感器测量导线周围电磁场分布,实现电流的非接触式测量方法是一种新型电流测量方法。因为测量误差受到干扰磁场以及磁传感器位置不确定性带来的影响,所以信号处理算法是提高测量精确度和实用性的关键。该文分别介绍了多传感器测量平行导线直流电流的3种算法;平均值法、空间付氏变换和最优卡尔曼滤波,并从测量精度、算法复杂度和灵活性的角度进行了对比。通过仿真和实验结果说明最优卡尔曼滤波在保证测量精度的条件下,利于简化计算过程,以及提高算法的灵活性。

It has been proposed to measure electric current in a non-contact way through processing the outputs of the magnetic sensors around the current flowing conductors. Signal processing algorithm is one of the key issues because it＇s capable of reducing the impact of the interference magnetic field and the uncertainty of the positions of the magnetic sensors on the measurement error. In this paper, three signal processing algorithms, including averaging approach, spatial Fourier transform and optimal Kalman filtering, are presented respectively. The approaches are investigated through their accuracy, complexity and flexibility. Both the computer simulations and the experiment results show that optimal Kalman filtering produces measurement results of satisfying accuracy with less computation and improved flexibility.