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dc.contributor.authorLopes, V
dc.contributor.authorTurra, A. E.
dc.contributor.authorMuller-Slany, H. H.
dc.contributor.authorBrunzel, F.
dc.contributor.authorInman, D. J.
dc.date.accessioned2014-05-20T15:28:10Z
dc.date.available2014-05-20T15:28:10Z
dc.date.issued2002-01-01
dc.identifier.citationProceedings of Imac-xx: Structural Dynamics Vols I and Ii. Bethel: Soc Experimental Mechanics Inc., v. 4753, p. 484-490, 2002.
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/11449/38038
dc.description.abstractThis paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.en
dc.format.extent484-490
dc.language.isoeng
dc.publisherSoc Experimental Mechanics Inc
dc.relation.ispartofProceedings of Imac-xx: Structural Dynamics Vols I and Ii
dc.sourceWeb of Science
dc.titleStructural health evaluation by optimization techinique and artificial neural networken
dc.typeTrabalho apresentado em evento
dcterms.rightsHolderSoc Experimental Mechanics Inc
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationUNESP, Dept Mech Engn, BR-13385000 Llha Solteira, SP, Brazil
dc.description.affiliationUnespUNESP, Dept Mech Engn, BR-13385000 Llha Solteira, SP, Brazil
dc.identifier.wosWOS:000176646000070
dc.rights.accessRightsAcesso aberto
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Engenharia, Ilha Solteirapt
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