dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversity of California
dc.date.accessioned2018-12-11T16:45:09Z
dc.date.available2018-12-11T16:45:09Z
dc.date.created2018-12-11T16:45:09Z
dc.date.issued2017-01-01
dc.identifierStructural Health Monitoring, v. 16, n. 1, p. 62-78, 2017.
dc.identifier1741-3168
dc.identifier1475-9217
dc.identifierhttp://hdl.handle.net/11449/169274
dc.identifier10.1177/1475921716662142
dc.identifier2-s2.0-85007137805
dc.identifier2-s2.0-85007137805.pdf
dc.description.abstractNonlinearities in the dynamical behavior of mechanical systems can degrade the performance of damage detection features based on a linearity assumption. In this article, a discrete Volterra model is used to monitor the prediction error of a reference model representing the healthy structure. This kind of model can separate the linear and nonlinear components of the response of a system. This property of the model is used to compare the consequences of assuming a nonlinear model during the nonlinear regime of a magneto-elastic system. Hypothesis tests are then employed to detect variations in the statistical properties of the damage features. After these analyses, conclusions are made about the application of Volterra series in damage detection.
dc.languageeng
dc.relationStructural Health Monitoring
dc.relation0,849
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectDamage detection
dc.subjectdiscrete-time Volterra series
dc.subjectnonlinear dynamics
dc.subjectstatistical hypothesis testing
dc.subjectsystem identification
dc.titleOn the application of discrete-time Volterra series for the damage detection problem in initially nonlinear systems
dc.typeArtículos de revistas


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