Fault Diagnostic method of High-current Converter Using Wavelet Neural Network Based on Improved Adaptive Genetic Algorithms

摘要

A novel method for fault Diagnosis of High-current converter, which is constructed on the basis of Wavelet Neural Network and Improved Adaptive Genetic Algorithms (IAGA), is presented here. In the proposed method, IAGA is employed to optimize the structure and the parameters of WNN and enhance the complexity, convergence and generalization ability of the network. By training and testing under MATLAB/SIMULINK, it is clearly shown that WNN based on IAGA performs better than WNN based on BP (Back-Propagation Neural Network) as well as linear adaptive GA (LAGA).