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Article: On-line fault diagnosis based on B-spline neural networks using asymptotic local approach

TitleOn-line fault diagnosis based on B-spline neural networks using asymptotic local approach
Authors
KeywordsAsymptotic local approach
Fault diagnosis
Neural network
Residual method
Issue Date2001
PublisherChinese Automatic Control Society. The Journal's web site is located at http://www.wiley.com/bw/journal.asp?ref=1561-8625
Citation
Asian Journal of Control, 2001, v. 3 n. 1, p. 73-78 How to Cite?
AbstractFault diagnosis is crucial in monitoring industrial processes. Faults can be often detected from residuals generated from the system model. For systems with known models, residuals can be readily generated. However, for systems with unknown models, neural networks can be used to model the system. For small or incipient faults, it is difficult to detect faults directly from the residuals. The asymptotic local approach, which transforms the fault diagnosis problem into one that detects statistical changes in a random variable, is proposed. The proposed scheme is illustrated by a simulation example, and comparison with faults obtained directly from the residuals is also made.
Persistent Identifierhttp://hdl.handle.net/10722/156588
ISSN
2015 Impact Factor: 1.407
2015 SCImago Journal Rankings: 0.862
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Yen_HK
dc.contributor.authorChan, CWen_HK
dc.contributor.authorCheung, KCen_HK
dc.date.accessioned2012-08-08T08:43:05Z-
dc.date.available2012-08-08T08:43:05Z-
dc.date.issued2001en_HK
dc.identifier.citationAsian Journal of Control, 2001, v. 3 n. 1, p. 73-78en_HK
dc.identifier.issn1561-8625en_HK
dc.identifier.urihttp://hdl.handle.net/10722/156588-
dc.description.abstractFault diagnosis is crucial in monitoring industrial processes. Faults can be often detected from residuals generated from the system model. For systems with known models, residuals can be readily generated. However, for systems with unknown models, neural networks can be used to model the system. For small or incipient faults, it is difficult to detect faults directly from the residuals. The asymptotic local approach, which transforms the fault diagnosis problem into one that detects statistical changes in a random variable, is proposed. The proposed scheme is illustrated by a simulation example, and comparison with faults obtained directly from the residuals is also made.en_HK
dc.languageengen_US
dc.publisherChinese Automatic Control Society. The Journal's web site is located at http://www.wiley.com/bw/journal.asp?ref=1561-8625en_HK
dc.relation.ispartofAsian Journal of Controlen_HK
dc.subjectAsymptotic local approachen_HK
dc.subjectFault diagnosisen_HK
dc.subjectNeural networken_HK
dc.subjectResidual methoden_HK
dc.titleOn-line fault diagnosis based on B-spline neural networks using asymptotic local approachen_HK
dc.typeArticleen_HK
dc.identifier.emailChan, CW: mechan@hkucc.hku.hken_HK
dc.identifier.emailCheung, KC: kccheung@hkucc.hku.hken_HK
dc.identifier.authorityChan, CW=rp00088en_HK
dc.identifier.authorityCheung, KC=rp01322en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0035263971en_HK
dc.identifier.hkuros59081-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0035263971&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3en_HK
dc.identifier.issue1en_HK
dc.identifier.spage73en_HK
dc.identifier.epage78en_HK
dc.publisher.placeTaiwanen_HK
dc.identifier.scopusauthoridWang, Y=7601487533en_HK
dc.identifier.scopusauthoridChan, CW=7404814060en_HK
dc.identifier.scopusauthoridCheung, KC=7402406698en_HK

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