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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73036
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dc.contributor.authorLopes, V.-
dc.contributor.authorGonsalez, C. G.-
dc.contributor.authorDa Silva, S.-
dc.contributor.authorRoy, S.-
dc.contributor.authorKode, K.-
dc.contributor.authorSunor, F.-
dc.contributor.authorChang, F. K.-
dc.date.accessioned2014-05-27T11:26:19Z-
dc.date.accessioned2016-10-25T18:36:15Z-
dc.date.available2014-05-27T11:26:19Z-
dc.date.available2016-10-25T18:36:15Z-
dc.date.issued2011-12-01-
dc.identifier.citationStructural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring, v. 1, p. 1196-1205.-
dc.identifier.urihttp://hdl.handle.net/11449/73036-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73036-
dc.description.abstractStructural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.en
dc.format.extent1196-1205-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectCritical challenges-
dc.subjectDamage effects-
dc.subjectData sets-
dc.subjectEnvironmental conditions-
dc.subjectInduced damage-
dc.subjectPractical implementation-
dc.subjectPZT-
dc.subjectSensor data-
dc.subjectSensor measurements-
dc.subjectAluminum-
dc.subjectFuzzy clustering-
dc.subjectIntelligent structures-
dc.subjectMaintenance-
dc.subjectPiezoelectric transducers-
dc.subjectSensors-
dc.titleCharacterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clusteringen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionCentro de Engenharias e Ciências Exatas (CECE)-
dc.contributor.institutionStanford University-
dc.description.affiliationUniv Estadual Paulista UNESP, Ilha Solteira, SP-
dc.description.affiliationWestern Paraná State University (UNIOESTE) Centro de Engenharias e Ciências Exatas (CECE), Foz do Iguaçu, PR-
dc.description.affiliationDepartment of Aeronautics and Astronautics Stanford University-
dc.description.affiliationDepartment of Computational and Mathematical Engineering Stanford University-
dc.description.affiliationUnespUniv Estadual Paulista UNESP, Ilha Solteira, SP-
dc.identifier.wosWOS:000297634100145-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofStructural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring-
dc.identifier.scopus2-s2.0-84866648665-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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