Pattern recognition for partial discharge in GIS based on pulse coupled neural networks and wavelet packet decomposition

Based on the characteristics of partial discharge (PD) defects in gas insulated switchgear (GIS), four typical single defects were designed for the present paper. PD three-dimensional (3D) patterns were constructed based on the ultra high frequency detection systems. The pulse-coupled neural networks (PCNN) and wavelet packet decomposition (WPD) method were used in PD feature extraction. The recognition results show that the proposed method used in PD feature extraction can effectively improve the accuracy of pattern recognition rate. Streszczenie. Przeanalizowano defekty wylącznika gazowego z wyladowaniem niezupelnym. Defekty te przedstawiane są jako obrazy 3D. Do ekstrakcji cech tych obrazow wykorzystuje sie transformate falkową i impulsowo sprzezone sieci neuronowe. (Rozpoznawanie cech wyladowania niezupelnego w wylącznikach gazowych z wykorzystaniem impulsowo sprzezonych sieci neuronowych i transformaty falkowej)

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