基于小波分析的故障电弧检测方法

Arc Fault Detection Based on Wavelet Analysis

为了对配电系统中常见的故障电弧实现快速可靠诊断,进而采取有效的保护措施,笔者提出一种基于多分辨分析的快速小波变换分析提取故障电弧特征频段的诊断方法,利用基于非参数自适应估计理论的Birge-Massart策略进行阀值求解,结合小波阀值降噪解功能对电弧电流进行降噪处理。根据小波分析适于分析非平稳信号的特点,采用该分析方法检测不同类型负载下电弧电流中的奇异信号。综合实验数据,分析表明该方法能有效地实现对故障电弧的诊断。

For the purpose of quick and reliable diagnosis of arc fault which occurs frequently in power distribution system and taking effective protection measures,this paper presents a method of analyzing and extracting the characteristic frequency bands of the arc fault current on the basis of the fast wavelet transform with multiresolution analysis.The signal of arc fault current is denoised using the threshold denoising method combining with Birge-Massart threshold value strategy which is based on the non-parametric adaptive estimation theory.The wavelet decomposition,which is suitable for analyzing non-stationary signals,is adopted to detect the singularity of arc fault currents under different types of load.The analysis combining with experiment data shows this method can detect the arc fault effectively.