Study on information fusion based on wavelet neural network and evidence theory in fault diagnosis

被引：0

作者：

Feng Dengchao ^{[1
]}

Pereira, J. M. Dias ^{[1
]}

机构：

[1] Escola Superior Tecnol IPS, Rua Vale Chaves, P-2910761 Setubal, Portugal

来源：

ICEMI 2007: PROCEEDINGS OF 2007 8TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL III | 2007年

关键词：

wavelet neural network; fault diagnosis; evidence theory; fuzzy;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

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.

引用

页码：522 / +

页数：3

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