基于粒子滤波的光学电流互感器信号处理方法研究

摘要

有效滤除噪声，提高信噪比（SNR）和测量精度是光学电流互感器(OCT)信号处理的重要环节。介绍了基于法拉第效应的光学电流互感器的基本原理和信噪特性。针对光学电流互感器低信噪比的特性，提出了采用粒子滤波的方法来从时域的角度提高输出信噪比。在被测电流为直流和交流两种情况下，分别建立合适的滤波动态空间模型，选择合适的参数后采用裂变自举粒子滤波算法（FBPF）在Matlab上进行两种情况下的仿真验证，结果表明粒子滤波算法能够有效地提高输出信噪比和测量精度。%Effectively filtering out noise and improving the signal-to-noise ratio (SNR) and measurement accuracy is essential in signal processing for optical current transducers (OCT). This paper introduces the principle and SNR characteristics of OCT which is based on the Faraday Magneto-optic effect, and proposes a particle filtering method to address the problem of low SNR of OCT. In the verification on the simulation platform of MATLAB, a particle filtering dynamic model is established and a fission bootstrap particle filter (FBPF) algorithm with proper parameters is implemented, for direct current and alternative current respectively. The results indicate that the proposed method effectively improves SNR and measurement accuracy. This work is supported by National Natural Science Foundation of China (No. 51277066).