Abstract
Identification of nonlinear dynamical systems have enjoyed significant progression over the past few years with the outcome of various developed identificationmethods, however there is still no generalised method applicable to structures with arbitrary nonlinearity. In the analysis of nonlinear dynamical system, it is essential to establish accurate and reliable tools that are capable of estimating the parameters from measured data for both the linear and nonlinear system. This paper presents a modular framework approach for upgrading a valid linear finite element structural model to accommodate any nonlinearities present in a system. To validate the efficiency of the proposed method, numerical and experimental studies are conducted on a “Multiple Beam Test Structure”, the method uses an iterative process to upgrade the nonlinear terms in the system. The results are verified by comparing predicted new response with measured data.
Original language | English |
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Title of host publication | Nonlinear Dynamics |
Subtitle of host publication | Proceedings of the 34th IMAC, A Conference and Exposition on Structural Dynamics 2016 |
Editors | Gaetan Kerschen |
Place of Publication | Cham |
Publisher | Springer |
Pages | 203-217 |
Number of pages | 15 |
Volume | 1 |
ISBN (Electronic) | 978-3-319-29739-2 |
ISBN (Print) | 978-3-319-29738-5 |
DOIs | |
Publication status | Published - 2016 |
Externally published | Yes |
Event | 34th Conference and Exposition on Structural Dynamics, IMAC 2016 - Orlando, United States Duration: 25 Jan 2016 → 28 Jan 2016 Conference number: 34 |
Publication series
Name | Conference Proceedings of the Society for Experimental Mechanics Series |
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Publisher | Springer |
ISSN (Print) | 2191-5644 |
ISSN (Electronic) | 2191-5652 |
Conference
Conference | 34th Conference and Exposition on Structural Dynamics, IMAC 2016 |
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Abbreviated title | IMAC |
Country/Territory | United States |
City | Orlando |
Period | 25/01/16 → 28/01/16 |
Keywords
- Finite element
- Model upgrading
- Nonlinearities
- Structural models and framework