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.
关键词
时频分析/馈线终端/自动化/联调测试/能量谱特征/混频信号
Key words
time-frequency analysis/feeder terminals/automation/joint debugging test/energy spectrum characteristics/mixing signal
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