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.
Electric Power System Wavelet Theory Back Propagation Neural Network (BPNN) Gas Insulated Switchgear (GIS) Partial Discharge (PD)
WANG Xiaozhe WANG Jinping DAI Huaizhi LI Yuexian
College of Information Science and Engineering, Northeastern University, Shenyang 110001, China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
1454-1457
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）