Discrimination of Multi-PD sources using wavelet 2D compression for T-F distribution of PD pulse waveform

부분방전 펄스파형의 시간-주파수분포의 웨이블렛 2D 압축기술을 이용한 복합부분방전원의 식별

PD(Partial Discharge) signal emitted from PD sources has their intrinsic features in the region of time and frequency. STFT(Short Time Fourier Transform) shows time-frequency distribution at the same time. 2-Dimensional matrices(33${\times}$77) from STFT for PD pulse signals are a good feature vectors and can be decreased in dimension by wavelet 2D data compression technique. Decreased feature vectors(13${\times}$24) were used as inputs of Back-propagation ANN(Artificial Neural Network) for discrimination of Multi-PD sources(air discharge sources(3), surface discharge(1)). They are a good feature vectors for discriminating Multi-PD sources.