Reference : Nonlinear model updating by means of identified nonlinear normal modes
Scientific congresses and symposiums : Unpublished conference/Abstract
Engineering, computing & technology : Aerospace & aeronautics engineering
http://hdl.handle.net/2268/181450
Nonlinear model updating by means of identified nonlinear normal modes
English
Song, Mingming [Tufts University > Department of Civil and Environmental Engineering > > >]
Renson, Ludovic mailto [Université de Liège > > R&D Direction : Chercheurs ULg en mobilité >]
Noël, Jean-Philippe mailto [Université de Liège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Moaveni, Babak [Tufts University > Department of Civil and Environmental Engineering > > >]
Kerschen, Gaëtan mailto [Université de Liège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux >]
Jun-2015
No
No
International
Engineering Mechanics Institute Conference
du 16 juin au 19 juin 2015
Palo Alto (Stanford)
CA
[en] Nonlinear model updating ; Nonlinear system identification ; Nonlinear normal modes
[en] Modal parameters are the most common features used for linear model updating. Although the modal analysis theory does not hold for nonlinear dynamic systems, its popularity encouraged researchers to come up with an equivalent version of normal modes for nonlinear systems, i.e., nonlinear normal modes (NNMs). A nonlinear system vibrates in NNMs when all masses have periodic motions of the same period, and at any time, the position of all the masses is uniquely defined by the position of any one of them. This paper investigates the feasibility of nonlinear model updating by minimizing the difference between the model-predicted and measured/identified nonlinear normal modes. A two degree-of-freedom mass-spring system with three linear springs and a cubic nonlinear spring is considered as the case study. The energy-dependent natural frequency and NNM of the first vibration mode of the system are identified at three different levels of energy. The stiffness parameters of the system are estimated by minimizing an objective function which is defined as the discrepancy between model-predicted natural frequency and NNM of the first mode, and their identified counterparts at the three measured energy levels. Performance of the proposed updating approach is evaluated at different levels of noise and different levels of modeling errors (i.e., nonlinear model classes).
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS ; Union Européenne = European Union - UE = EU
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/181450

There is no file associated with this reference.

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.