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dc.creatorBorges, Fernando Elias de Melo-
dc.creatorPinto, Andrey Willian Marques-
dc.creatorPereira, Daniel Augusto-
dc.creatorBarbosa, Bruno Henrique Groenner-
dc.creatorMagalhães, Ricardo Rodrigues-
dc.creatorFerreira, Danton Diego-
dc.creatorBarbosa, Tássio Spuri-
dc.date.accessioned2020-08-14T18:48:44Z-
dc.date.available2020-08-14T18:48:44Z-
dc.date.issued2020-
dc.identifier.citationBORGES, F. E. de M. et al. Higher-Order Statistics and support vector machines applied to fault detection in a cantilever beam. Theoretical and Applied Engineering, Lavras, v. 4, n. 1, p. 1-8, 2020..pt_BR
dc.identifier.urihttp://www.taaeufla.deg.ufla.br/index.php/TAAE/article/view/30pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/42430-
dc.description.abstractIn this paper, it is proposed a method to detect structural faults or damages using Higher-Order Statistics (HOS). For this, vibration signals were taken from cantilever beams. Such vibrations were generated by a DC motor with varying rotation, generating vibrations at various frequencies. Vibration signals and engine speed control were performed by an Arduino board. After the signal acquisition, parameters are extracted by means of second-, third- and fourthorder cumulants and then the most relevant ones were selected by the Fisher’s Discriminant Ratio (FDR). To fault detection, a Support Vector Machine (SVM) classifier has been designed in its One-Class version, where only oneclass knowledge is required. The results showed a good ability to represent vibration signals via HOS along with a large reduction in dimensionality given using FDR and a good generalization by means of the SVM classifier. Failure detection results showed 100% success rates.pt_BR
dc.languageenpt_BR
dc.publisherUniversidade Federal de Lavraspt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceTheoretical and Applied Engineeringpt_BR
dc.subjectVibration analysispt_BR
dc.subjectStructural health monitoringpt_BR
dc.subjectOne-Class learningpt_BR
dc.subjectAnálise de vibraçãopt_BR
dc.subjectMonitoramento de integridade estruturalpt_BR
dc.subjectDetecção de falhaspt_BR
dc.subjectMáquina de vetores de suportept_BR
dc.subjectFunção discriminante de Fisherpt_BR
dc.titleHigher-Order Statistics and support vector machines applied to fault detection in a cantilever beampt_BR
dc.typeArtigopt_BR
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