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Modified Morlet wavelet neural networks for fault detection
Guo QJ(郭前进); Yu HB(于海斌); Xu AD(徐皑冬)
Department工业控制系统研究室
Conference Name5th International Conference on Control and Automation
Conference DateJune 26-29, 2005
Conference PlaceBudapest, HUNGARY
Author of SourceIEEE Control Chapter, Singapore, IEEE Ind Applicat Chapter, Hungary
Source Publication2005 International Conference on Control and Automation (ICCA), Vols 1 and 2
PublisherIEEE
Publication PlaceNEW YORK
2005
Pages1209-1214
Indexed ByEI ; CPCI(ISTP)
EI Accession number2005489505875
WOS IDWOS:000232156500216
Contribution Rank1
ISBN0-7803-9137-3
Abstract

Wavelet neural networks (WNN) combining the properties of the wavelet transform and the advantages of artificial neural networks (ANNs) have attracted great interest and become a popular tool for various fields of mathematics and engineering. We describe here the application of the modified Morlet based WNN to the fault detection of rotating machinery. The activation functions of the wavelet nodes in the hidden layer are derived from a modified Morlet mother wavelet. In this paper, the wavelet network architecture for intelligent fault detection is first introduced. Then an optimization method of neural network and a training algorithm is developed. Finally, feedforward backpropagation neural network (BP) and wavelet neural networks are compared for fault detection. The aim of this study is to examine the effective of the modified Morlet WNN model for fault detection. Experiment results shows that the modified Morlet WNN has advantages of rapid training, generality and accuracy over feedforward backpropagation neural network.

Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/8103
Collection工业信息学研究室_工业控制系统研究室
Corresponding AuthorYu HB(于海斌)
AffiliationShenyang Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Guo QJ,Yu HB,Xu AD. Modified Morlet wavelet neural networks for fault detection[C]//IEEE Control Chapter, Singapore, IEEE Ind Applicat Chapter, Hungary. NEW YORK:IEEE,2005:1209-1214.
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