PD Pattern Recognition Using Complex Wavelet Transform Coefficient As The Feature
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Abstract:
Complex wavelet transform can characterize the partial feature of the PD signal in time-domain and frequency-domain,and provides the unique phasic information.In this paper,the PD pulse waveforms which are created by 4 typical insulated defects are transformed by complex wavelet,and then the complex wavelet coefficient's real part,imaginary part and compound coefficient are clustered by the Fuzzy c-means,the energy of the cluster is the feature of pattern recognition.Discharge samples are got through large number of experiments,and BPNN can identify the PD created by 4 typical insulated defects effectively.The results show that the feature extracted from compound coefficient is better than the feature extracted form the real part and imaginary part of complex wavelet coefficient or wavelet coefficient.