基于信号能量谱特征的局部放电故障识别方法及其系统实现

Method for Partial Discharge Pattern Recognition Based on Characteristics of Signal Energy Spectrum and Its System Realization

为解决传统超高频(ultra-high frequency,UHF)法实现局部放电(partial discharge,PD)故障模式识别对采样频率、传输带宽和处理速度要求苛刻的困难,提出一种基于信号能量谱特征的局部放电故障识别新方法。该方法通过提取局部放电超高频电磁波信号在不同频段的能量值,构建能量谱序列作为模式识别判据,能够有效降低局放信号对采样频率、传输带宽和处理速度的要求。其次通过5种典型空气绝缘缺陷局部放电试验获得了模式识别的初步判据,验证了该方法的有效性;基于该方法,应用射频理论构建了相应的信号处理系统,并再次通过局部放电试验构建了基于此系统的模式识别判断依据,最后通过验证性试验证明该系统的识别正确率基本达到90%。

Conventional partial discharge（PD） fault pattern recognition using ultra-high frequency（UHF） method has strict requirements of sample rate, transmission bandwidth, and processing speed. To solve this problem, we proposed a new method based on signal energy spectrum for PD pattern recognition. In this method, by extracting energy of PD＇s UHF electromagnetic signals in different frequency bands, we built the energy spectrum sequence as a criterion for pattern rec- ognition which could greatly reduce the recognition＇s demands for sample rate, bandwidth, and processing speed. Through PD experiments of five typical insulation defects, we obtained some basic recognition judgment that could prove the proposed method to be effective. Plus, using the method, we established a corresponding signal processing system based on radio frequency（RF） theory. Then through PD experiments, the recognition judgment of this system was also proposed. Further experiments indicated that the system has correct rate of 90% in recognition.