Method to Identify Developing Stages of Air-Gap Discharge in Oil-Paper Insulation Based on Cluster-Wavelet Neural Network

Based on air-gap within oil-paper insulation,a test platform was set up in laboratory to research air-gap discharge and its development stages.Using constant voltage method the experiments for developing characteristics of partial discharge were performed and 29 parameters of maximum discharge amplitudes,average discharge amplitudes and discharge times of phase resolved partial discharge(PRPD) as well as amplitude distributions of discharge were extracted;utilizing kernel principal component analysis,the different developing stages of partial discharge were divided by system clustering.A method based on cluster-wavelet neural network to identify developing stages of discharge was established.Identification results show that according to effective discharge characteristic quantities the proposed method can identify discharging stages well and the obtained results are basically conform to the results of system clustering analysis for the same data.