绝缘子泄漏电流在线监测自适应最优小波实时处理传输研究

Research on On-Line Monitoring of Insulator Leakage Current Based on Adaptive Optimal Wavelet Real-Time Processing Transmission

绝缘子泄漏电流能反映绝缘子工作状态,可对其进行数据挖掘处理。提出一种能量逐层最优小波去噪方法,该方法依据小波多尺度分解信号的能量,自适应选择与信号分解尺度匹配的最优小波进行信号去噪。首先通过搭建绝缘子泄漏电流试验平台采集原始泄漏电流信号,并采用标准软阈值方法对信号进行预处理,再将能量逐层最优小波去噪方法与相似系数逐层最优小波及标准软阈值法进行了比较。结果表明:能量逐层最优小波方法对不同信号具有自适应性,采用该方法去噪后对原信号畸变小,其去噪信号最为光滑,去噪所需时间短,利于绝缘子泄漏电流信号的实时传输,具有较好的去噪效果和实用价值。

The insulator leakage current could reflect the working state of the insulator,and it can be processed by data mining.An energy layer-wise optimal wavelet de-noising method was proposed to de-noise the leakage current of insulators.This method adaptively selected the optimal wavelet that matched the signal decomposition scale for signal de-noising based on the energy of the wavelet multiscale decomposition signal.First,an insulator leakage current acquisition test platform was set up in the laboratory to collect the original leakage current signal,and the signal was pre-processed using the standard soft threshold method.Then the energy layer-wise optimal wavelet de-noising method and the similarity coefficient layer-by-layer optimal wavelet and standard soft threshold method were used to compare the effect.The results showed that the signal distortion was smallest after denoising using the energy based wavelet selected method.The de-noising signal was the smoothest and the time required for de-noising was the shortest.Thismethod had very good de-noising effect and practical value.