基于小波变换与差值能量法相结合的串联故障电弧检测方法

Arc Fault Detection based on Wavelet Transform and Difference-energy

由于低压用户端交流串联电弧故障回路电流幅值小、一些电力电子负载正常工作电流与串联电弧故障电流相似等原因,使得故障电弧的准确诊断十分困难。本文提出了一种基于小波变换与差值能量法相结合的串联电弧故障检测方法。对原始电流信号进行小波阈值去噪,运用Mallat快速算法对信号进行多分辨率分析,提取多分辨率分析结果中包含电弧信息较多、负载干扰信息较少的频段进行小波反变换;运用差值能量法对反变换后富含电弧信息的信号进行故障诊断。最后利用自制的实验设备验证了算法的准确性。

Because of the low current value of series arc fault in AC low voltage circuits and the normal current of some power electronic loads is similar to arc fault current, it is difficult to diagnose the series arc fault accurately. This paper presents a method of series arc fault analysis and diagnosis based on the wavelet transform and difference-energy. Mallat method is used to decompose the signals which are denoised by the wavelet threshold principle. Extract the layers in multi-resolution analysis results which contain much arc fault information and are not affected by the loads frequency for wavelet reconstruction. Then we apply the difference-energy method to diagnosis the signals after reconstruction. The accuracy of the algorithm is verified by the self-made experimental equipment.