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).

关键词： Fault Diagnosis High-current Converter WNN BP LAGA Improved Adaptive GA

作者: Chen Te-fang Fu Qiang Zhu Jiao-jiao

作者单位: School of Information Science and Engineering,Central South University,Changsha,China School of Traffic & Transportation Engineering,Central South University,Changsha,China

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System and Applied Material(2012智能系统与应用材料国际会议)(GSAM2012)

会议地点: 太原

会议语种:英文

页码: 1150-1155

在线出版日期: 2012-01-13（万方平台首次上网日期，不代表论文的发表时间）