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dc.contributor.authorKao, CYen_US
dc.contributor.authorHung, SLen_US
dc.date.accessioned2014-12-08T15:40:07Z-
dc.date.available2014-12-08T15:40:07Z-
dc.date.issued2003-11-01en_US
dc.identifier.issn0045-7949en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0045-7949(03)00323-7en_US
dc.identifier.urihttp://hdl.handle.net/11536/27400-
dc.description.abstractThis work presented a novel neural network-based approach for detecting structural damage. The proposed approach involves two steps. The first step, system identification, uses neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The second step, structural damage detection, uses the aforementioned trained NSINs to generate free vibration responses with the same initial condition or impulsive force. Comparing the periods and amplitudes of the free vibration responses of the damaged and undamaged states allows the extent of changes to be assessed. Furthermore, numerical and experimental examples demonstrate the feasibility of applying the proposed method for detecting structural damage. (C) 2003 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectneural networksen_US
dc.subjectstructural damage detectionen_US
dc.subjectfree vibration responsesen_US
dc.subjectsystem identificationen_US
dc.subjectshaking table testen_US
dc.subjectstructural health monitoringen_US
dc.titleDetection of structural damage via free vibration responses generated by approximating artificial neural networksen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0045-7949(03)00323-7en_US
dc.identifier.journalCOMPUTERS & STRUCTURESen_US
dc.citation.volume81en_US
dc.citation.issue28-29en_US
dc.citation.spage2631en_US
dc.citation.epage2644en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000186799500008-
dc.citation.woscount42-
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