Automatic Detection Method of Partial Discharge in Switchgear Based on Wavelet Packet Energy Spectrum and Neural Network
In order to reliably grasp the operating status of switchgear and accurately detect its partial discharge phe-nomenon,a wavelet packet energy spectrum and neural network based automatic detection method for switchgear par-tial discharge is proposed.This method adopts digital processing technology and fuzzy parameter recognition method to remove the mixed frequency signal in the signal and obtain a new operating signal of the switchgear.Using wavelet packet decomposition method to decompose the signal,while processing the noise signal in the signal,extract the energy spectrum feature of partial discharge,and input this feature into the radial basis function neural network to complete the classification and detection of partial discharge in the switchgear.The test results show that this method can effectively remove mixing signals and reduce signal noise.The distortion rate and distortion rate of the processed signal are extremely low,and the application performance is good.Can complete partial discharge signal detection for different categories of switchgear.
time-frequency analysisfeeder terminalsautomationjoint debugging testenergy spectrum characteristicsmixing signal
万方数据
维普
