dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | University of California | |
dc.date.accessioned | 2018-12-11T16:45:09Z | |
dc.date.available | 2018-12-11T16:45:09Z | |
dc.date.created | 2018-12-11T16:45:09Z | |
dc.date.issued | 2017-01-01 | |
dc.identifier | Structural Health Monitoring, v. 16, n. 1, p. 62-78, 2017. | |
dc.identifier | 1741-3168 | |
dc.identifier | 1475-9217 | |
dc.identifier | http://hdl.handle.net/11449/169274 | |
dc.identifier | 10.1177/1475921716662142 | |
dc.identifier | 2-s2.0-85007137805 | |
dc.identifier | 2-s2.0-85007137805.pdf | |
dc.description.abstract | Nonlinearities 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.language | eng | |
dc.relation | Structural Health Monitoring | |
dc.relation | 0,849 | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Damage detection | |
dc.subject | discrete-time Volterra series | |
dc.subject | nonlinear dynamics | |
dc.subject | statistical hypothesis testing | |
dc.subject | system identification | |
dc.title | On the application of discrete-time Volterra series for the damage detection problem in initially nonlinear systems | |
dc.type | Artículos de revistas | |