SIA OpenIR  > 工业信息学研究室  > 工业控制系统研究室
A method for condition monitoring and fault diagnosis in electromechanical system
Guo QJ(郭前进); Yu HB(于海斌); Hu JT(胡静涛); Xu AD(徐皑冬)
Department工业控制系统研究室
Source PublicationNeural Computing & Applications
ISSN0941-0643
2008
Volume17Issue:4Pages:373-384
Indexed BySCI ; CPCI(ISTP)
WOS IDWOS:000257124100007
Contribution Rank1
KeywordFault Diagnosis Electrical Machines Kernel Independent Component Analysis Kernel Trick Gaussian Chirplet Distributions Self-organizing Map
AbstractCondition monitoring of electrical machines has received considerable attention in recent years. Many monitoring techniques have been proposed for electrical machine fault detection and localization. In this paper, the feasibility of using a nonlinear feature extraction method noted as Kernel independent component analysis (KICA) is studied and it is applied in self-organizing map to classify the faults of induction motor. In nonlinear feature extraction, we employed independent component analysis (ICA) procedure and adopted the kernel trick to nonlinearly map the Gaussian chirplet distributions into a feature space. First, the adaptive Gaussian chirplet distributions are mapped into an implicit feature space by the kernel trick, and then ICA is performed to extract nonlinear independent components of the Gaussian chirplet distributions. A thorough laboratory study shows that the diagnostic methods provide accurate diagnosis, high sensitivity with respect to faults, and good diagnostic resolution.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence
WOS KeywordINDEPENDENT COMPONENT ANALYSIS ; SIGNAL ; MAPS ; ICA
WOS Research AreaComputer Science
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/6898
Collection工业信息学研究室_工业控制系统研究室
Corresponding AuthorGuo QJ(郭前进)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences
2.Graduate School of the Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Guo QJ,Yu HB,Hu JT,et al. A method for condition monitoring and fault diagnosis in electromechanical system[J]. Neural Computing & Applications,2008,17(4):373-384.
APA Guo QJ,Yu HB,Hu JT,&Xu AD.(2008).A method for condition monitoring and fault diagnosis in electromechanical system.Neural Computing & Applications,17(4),373-384.
MLA Guo QJ,et al."A method for condition monitoring and fault diagnosis in electromechanical system".Neural Computing & Applications 17.4(2008):373-384.
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