| Full text | |
| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Univ Estadual Paulista, UNESP, Fac Engn Ilha Solteira, Dept Engn Mecan, Av Brasil 56, BR-15385000 Ilha Solteira, SP - Brazil
[2] Univ Calif San Diego, Dept Struct Engn, 9500 Gilman Dr, La Jolla, CA 92093 - USA
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | MECHANICAL SYSTEMS AND SIGNAL PROCESSING; v. 128, p. 463-478, AUG 1 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
The damage detection problem becomes a more difficult task when the intrinsically nonlinear behavior of the structures and the natural data variation are considered in the analysis because both phenomena can be confused with damage if linear and deterministic approaches are implemented. Therefore, this work aims the experimental application of a stochastic version of the Volterra series combined with a novelty detection approach to detect damage in an initially nonlinear system taking into account the measured data variation, caused by the presence of uncertainties. The experimental setup is composed by a cantilever beam operating in a nonlinear regime of motion, even in the healthy condition, induced by the presence of a magnet near to the free extremity. The damage associated with mass changes in a bolted connection (nuts loosed) is detected based on the comparison between linear and nonlinear contributions of the stochastic Volterra kernels in the total response, estimated in the reference and damaged conditions. The experimental measurements were performed on different days to add natural variation to the data measured. The results obtained through the stochastic proposed approach are compared with those obtained by the deterministic version of the Volterra series, showing the advantage of the stochastic model use when we consider the experimental data variation with the capability to detect the presence of the damage with statistical confidence. Besides, the nonlinear metric used presented a higher sensitivity to the occurrence of the damage compared with the linear one, justifying the application of a nonlinear metric when the system exhibits intrinsically nonlinear behavior. (C) 2019 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 15/25676-2 - Robust damage detection in uncertain nonlinear systems |
| Grantee: | Luis Gustavo Giacon Villani |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |
| FAPESP's process: | 17/15512-8 - Applications of model identification of guided wave propagation in composite structures for damage prognosis |
| Grantee: | Samuel da Silva |
| Support Opportunities: | Scholarships abroad - Research |
| FAPESP's process: | 12/09135-3 - Structural health monitoring in nonlinear mechanical systems through Volterra models |
| Grantee: | Samuel da Silva |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| FAPESP's process: | 17/24977-4 - Experimental nonlinear damage detection in uncertain nonlinear systems |
| Grantee: | Luis Gustavo Giacon Villani |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate (Direct) |