Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

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dc.contributor.authorDemarchi, D.
dc.contributor.authorPereira, J. A.
dc.contributor.authorLopes, V
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T13:29:23Z
dc.date.available2014-05-20T13:29:23Z
dc.date.issued2000-01-01
dc.description.abstractThis work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.en
dc.description.affiliationUNESP, Dept Mech Engn, BR-15385000 Ilha Solteira, SP, Brazil
dc.description.affiliationUnespUNESP, Dept Mech Engn, BR-15385000 Ilha Solteira, SP, Brazil
dc.format.extent1584-1589
dc.identifierhttp://www.thieme-connect.com/ejournals/abstract/10.1055/s-2006-949983
dc.identifier.citationImac-xviii: A Conference on Structural Dynamics, Vols 1 and 2, Proceedings. Bethel: Soc Experimental Mechanics Inc., v. 4062, p. 1584-1589, 2000.
dc.identifier.issn0277-786X
dc.identifier.lattes0224087261544502
dc.identifier.urihttp://hdl.handle.net/11449/9907
dc.identifier.wosWOS:000086462600240
dc.language.isoeng
dc.publisherSoc Experimental Mechanics Inc
dc.relation.ispartofImac-xviii: A Conference on Structural Dynamics, Vols 1 and 2, Proceedings
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.titleNon-destructive evaluation tool for monitoring and detection of structural damage by using neural network.en
dc.typeTrabalho apresentado em evento
dcterms.rightsHolderSoc Experimental Mechanics Inc
unesp.author.lattes0224087261544502
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Ilha Solteirapt

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Artigos - Engenharia Mecânica - FEIS