基于小波分析信号特征频段能量变比的故障电弧诊断技术研究

Arc Fault Diagnosis Technology Based on the Analysis of Energy Variation of Signal's Characteristic Frequency Band with Wavelet Transform

为了分析和研究故障电弧的特性,进而快速及时地检测出电弧故障,以便快速切断故障线路,笔者提出一种利用小波变换来分析故障电弧电流特征频段能量变比的诊断方法,通过采用db5小波基函数分别对线路正常工作情况下电流信号和串联型故障电弧电流信号进行6层小波分解,从而提取正常情况下和故障电弧发生情况下的频带能量值及其前后的能量变比,其中d4、d5细节信号所在的频段为故障电弧的特征频带。利用此故障电弧的典型特征可以准确地实现对故障电弧的诊断,且该分析结论对于线性负载情况下的故障电弧诊断研究具有普适应意义。

For rapid detection of arc fault and immediate break of fault lines,this paper presents a diagnostic method using wavelet transform to analyze the energy variation of the arc fault current in characteristic frequency bands. Adopting db5 wavelet function to decompose both the current in normal operation and the current of series arc fault into 6 layers,the energy variation of the arc fault current and the normal current in characteristic frequency bands is accordingly obtained. The frequency bands where detailed wavelet signals d4 and d5 exist can represent the specific character of the arc fault current. With this specific character,the arc fault can be accurately diagnosed. This present arc fault diagnosis technology is especially applicable to the arc fault with linear loads.