Monitoring and fault identification in aeronautical structures using an artmap-fuzzy-wavelet artificial neural network

dc.contributorMechanical Engineering Department, Ilha Solteira (FEIS)
dc.contributorElectrical Engineering Department, Ilha Solteira (FEIS)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T16:57:47Z
dc.date.available2018-12-11T16:57:47Z
dc.date.created2018-12-11T16:57:47Z
dc.date.issued2014-01-01
dc.identifierAdvanced Materials Research, v. 1025-1026, p. 1107-1112.
dc.identifier1662-8985
dc.identifier1022-6680
dc.identifierhttp://hdl.handle.net/11449/171934
dc.identifier10.4028/www.scientific.net/AMR.1025-1026.1107
dc.identifier2-s2.0-84937194271
dc.identifier2-s2.0-84937194271.pdf
dc.identifier2-s2.0-84937194271.pdf
dc.identifier5434299135943285
dc.identifier5434299135943285
dc.description.abstractThis paper presents a methodology to perform the monitoring and identification of flaws in aircraft structures using an ARTMAP-Fuzzy-Wavelet artificial neural network. This technique is used in the detection and characterization of structural failure. The main application of this method is to assist in the inspection of aircraft structures in order to identify and characterize failures as well as decision-making, in order to avoid accidents or air crashes. In order to evaluate this method, the modeling and simulation of signals from a numerical model of an aluminum beam was performed. The results obtained by the method are satisfactory compared to literature.
dc.languageeng
dc.relationAdvanced Materials Research
dc.relation0,121
dc.relation0,121
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectAeronautical structures
dc.subjectARTMAP-fuzzy-wavelet
dc.subjectIntelligence computation
dc.subjectMonitoring and fault identification
dc.titleMonitoring and fault identification in aeronautical structures using an artmap-fuzzy-wavelet artificial neural network
dc.typeActas de congresos


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