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Conference Paper: Fault detection of redundant systems based on B-spline neural network

TitleFault detection of redundant systems based on B-spline neural network
Authors
KeywordsFault detection
Redundant systems
Neural networks
B-spline functions
Issue Date2000
PublisherIEEE.
Citation
American Control Conference, Chicago, IL, USA, 28-30 June 2000, v. 2, p. 1215-1219 How to Cite?
AbstractThe fault detection and isolation of redundant sensor systems based on B-spline neural networks is presented in this paper. The network is trained using an algorithm with an adaptive learning rate. To further save computation time, the residual vector is transformed from a multivariate B-spline function to an univariate B-spline function. The detection of abrupt and drifting faults using the proposed method is discusses. The performance of the proposed method is illustrated by an example involving a redundant system consisting of six sensors.
Persistent Identifierhttp://hdl.handle.net/10722/46655
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorJin, Hongen_HK
dc.contributor.authorChan, CWen_HK
dc.contributor.authorZhang, HYen_HK
dc.contributor.authorYeung, WKen_HK
dc.date.accessioned2007-10-30T06:55:13Z-
dc.date.available2007-10-30T06:55:13Z-
dc.date.issued2000en_HK
dc.identifier.citationAmerican Control Conference, Chicago, IL, USA, 28-30 June 2000, v. 2, p. 1215-1219en_HK
dc.identifier.isbn0-7803-5519-9en_HK
dc.identifier.issn0743-1619en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46655-
dc.description.abstractThe fault detection and isolation of redundant sensor systems based on B-spline neural networks is presented in this paper. The network is trained using an algorithm with an adaptive learning rate. To further save computation time, the residual vector is transformed from a multivariate B-spline function to an univariate B-spline function. The detection of abrupt and drifting faults using the proposed method is discusses. The performance of the proposed method is illustrated by an example involving a redundant system consisting of six sensors.en_HK
dc.format.extent425670 bytes-
dc.format.extent5145 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofProceedings of the American Control Conferenceen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectFault detectionen_HK
dc.subjectRedundant systemsen_HK
dc.subjectNeural networksen_HK
dc.subjectB-spline functionsen_HK
dc.titleFault detection of redundant systems based on B-spline neural networken_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0-7803-5519-9&volume=2&spage=1215&epage=1219&date=2000&atitle=Fault+detection+of+redundant+systems+based+on+B-spline+neural+networken_HK
dc.identifier.emailChan, CW: mechan@hkucc.hku.hken_HK
dc.identifier.authorityChan, CW=rp00088en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ACC.2000.876693en_HK
dc.identifier.scopuseid_2-s2.0-0034541970en_HK
dc.identifier.hkuros49559-
dc.identifier.volume2en_HK
dc.identifier.spage1215en_HK
dc.identifier.epage1219en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridJin, Hong=34770583400en_HK
dc.identifier.scopusauthoridChan, CW=7404814060en_HK
dc.identifier.scopusauthoridZhang, HY=7409196387en_HK
dc.identifier.scopusauthoridYeung, WK=24345897100en_HK

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