Study on Information Fusion Based on Wavelet Neural Network and Evidence Theory in Fault Diagnosis

摘要：

Aimed at the low diagnosis accuracy of traditional fault diagnosis algorithm, information fusion algorithm based on wavelet neural network and evidence theory is proposed. In the initial diagnosis stage, wavelet neural network is used to improve the fault diagnosis ability of the local diagnosis networks. In the decision diagnosis stage, information fusion frame based on wavelet neural network and evidence theory is constructed to improve the accuracy of fault diagnosis by virtue of various redundant and complementary fault information. Simulation experiment results show the efficiency of the algorithm.

关键词： wavelet neural network fault diagnosis evidence theory fuzzy

作者: Feng Dengchao J.M.Dias Pereira

作者单位: School of Electronic & Information Engineering,Tianjin University,Tianjin 300072 China Escola Superior de Tecnologia do IPS,Rua do Vale de Chaves,Estefanilha,2910-761 Setúbal,Portugal

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）