Intelligent Faults Diagnosis Technology of the Power Transformer Based on the Wavelet Neural Network
it is analyzed the application of wavelet neural networks (WNN) in power transformer faults diagnosis. A WNN model is builded, transformer oil color spectrum analysis is taken input and output is fault type. With more degree of freedom in relation to the general neural network, wavelet neural network is in possession of more vivid and more valid ability in function approximation. With the good partial characteristic and distinguish rate learning wavelet neural network realizes the signal with good matching, and then wavelet neural network had stronger self adaptation ability, more sooner convergence rate and higher calculate accuracy. The test results of fault examples show that the effectiveness and potential applicable worthiness.
Zhijie Wang Chonglin Wang Yufa Xu
School of Electrical Engineering Shanghai dianji University Shanghai, 221008 P. R. China;School of I School of Information and Electrical Engineering China University of Mining and Technology Xuzhou, 2 School of Electrical Engineering Shanghai dianji University Shanghai, 221008 P. R. China
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）