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Cited 8 time in webofscience Cited 8 time in scopus
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Non-baseline Damage Detection Based on the Deviation of Displacement Mode Shape Data

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dc.contributor.authorKim, Jin-Bong-
dc.contributor.authorLee, Eun-Taik-
dc.contributor.authorRahmatalla, Salam-
dc.contributor.authorEun, Hee-Chang-
dc.date.available2019-03-09T02:01:44Z-
dc.date.issued2013-03-
dc.identifier.issn0195-9298-
dc.identifier.issn1573-4862-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/14790-
dc.description.abstractThe early detection of damage and structural health monitoring should be an important process for structural maintenance. The baseline information of the structural reference state is not available since the structure was not instrumented prior to the damage. This work offers a global-deviation approach to detect damage by measured data only without available data at the intact state. This work shows that the damage exists at the measurement locations to represent large and abrupt variation deviated from global mode shape curve. The proposed method is compared with the GSM (Gapped-Smoothing Method) provided by Ratcliffe and Bagaria and its superiority and effectiveness are illustrated in a numerical simulation and an experiment.-
dc.format.extent11-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER/PLENUM PUBLISHERS-
dc.titleNon-baseline Damage Detection Based on the Deviation of Displacement Mode Shape Data-
dc.typeArticle-
dc.identifier.doi10.1007/s10921-012-0154-8-
dc.identifier.bibliographicCitationJOURNAL OF NONDESTRUCTIVE EVALUATION, v.32, no.1, pp 14 - 24-
dc.description.isOpenAccessN-
dc.identifier.wosid000315045700002-
dc.identifier.scopusid2-s2.0-84874112617-
dc.citation.endPage24-
dc.citation.number1-
dc.citation.startPage14-
dc.citation.titleJOURNAL OF NONDESTRUCTIVE EVALUATION-
dc.citation.volume32-
dc.type.docTypeArticle-
dc.publisher.location미국-
dc.subject.keywordAuthorMode shape-
dc.subject.keywordAuthorContinuous system-
dc.subject.keywordAuthorDamage detection-
dc.subject.keywordAuthorNon-baseline data-
dc.subject.keywordAuthorFrequency domain-
dc.subject.keywordPlusFREQUENCY-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalWebOfScienceCategoryMaterials Science, Characterization & Testing-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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