Feature Extraction of Cable Partial Discharge Signal based on DT-CWT_Hankel_SVD

In order to identify the type of cable partial discharge Signal, it is necessary to extract the characteristics of its high-frequency signal. In this paper, we first proceed to analyze signal based on dual-tree complex wavelet transform. Then we use magnitude to build Hankel Matrix when we get complex wavelet coefficient and extract singularity signal by Singular value decomposition(SVD). To accomplish getting and recognizing features of PD, we set maximum singular value, average singular value and information entropy as characteristic quantity to analyze its distribution. The artificially simulated metal powder PD signal and standard PD signal are calculated and analyzed. The results show that the method is feasible.