You are here:
| Reference : Non-Linear Identification in Modal Space Using a Genetic Algorithm Approach for Model Se... |
| Scientific journals : Article | |||
| Engineering, computing & technology : Mechanical engineering Engineering, computing & technology : Aerospace & aeronautics engineering | |||
| http://hdl.handle.net/2268/6206 | |||
| Non-Linear Identification in Modal Space Using a Genetic Algorithm Approach for Model Selection | |
| English | |
| Platten, Michael F [ > > ] | |
| Wright, Jan Robert [University of Manchester > School of Mechanical, Aerospace and Civil Engineering > > >] | |
| Worden, Keith [University of Sheffield > Department of Mechanical Engineering > > >] | |
Dimitriadis, Grigorios  [Université de Liège - ULg > Département d'aérospatiale et mécanique > Intéractions fluide structure et aérodynamique expérimentale >] | |
| Cooper, Jonathan E [University of Manchester > School of Mechanical, Aerospace and Civil Engineering > > >] | |
| 2007 | |
| International Journal of Applied Mathematics & Mechanics | |
| GBS Publishers & Distributors (India) | |
| 3 | |
| 1 | |
| 72-89 | |
| International | |
| 0973-0184 | |
| [en] Nonlinear system identification ; modal analysis ; genetic algorithms | |
| [en] The Non-Linear Resonant Decay Method is an approach for the identification of non-linear
systems with large numbers of degrees of freedom. The identified non-linear model is expressed in linear modal space and comprises the modal model of the underlying linear system with additional terms representing the non-linear behaviour. Potentially, a large number of these non-linear terms will exist but not all of them will be significant. The problem of deciding which and how many terms are required for an accurate identification has previously been addressed using the Forward Selection and Backward Elimination techniques. In this paper, a Genetic Algorithm optimisation is proposed as an alternative to those methods. A simulated lumped parameter non-linear dynamic system is used to demonstrate the proposed optimisation. The use of separate data sets for the identification and validation of the modal model is also investigated. It is found that the Genetic Algorithm approach yields significantly better results than the Backward Elimination and Forward Selection algorithms in many cases. | |
| http://hdl.handle.net/2268/6206 | |
| http://ijamm.bc.cityu.edu.hk/ijamm/wp_home_download_this.asp?pn=82 |
| File(s) associated to this reference | ||||||||||||||
|
Fulltext file(s):
| ||||||||||||||
All documents in ORBi are protected by a user license.
