Research on fault signals recognition in GIS based on wavelet theory

According to the characteristics of partial discharge (PD) signals of gas insulated switchgear (GIS), a fault type recognition method based on wavelet packet transform is put forward. First the wavelet packet decomposition tree of PD signals is constructed. Then in feature extraction of PD signals, different data fusion algorithms are used in feature vector dimension reduction to enhance sensitivity of feature vector to PD fault signals characteristics. A fault recognizer based on back propagation neural network (BPNN) is designed. The results of simulation show that the wavelet transform based GIS fault signal recognition method is effective.