Locating nonlinearity in mechanical systems: a dynamic network perspective

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Abstract

Though it is a crucial step for most identification methods in nonlinear structural dynamics, nonlinearity location is a sparsely addressed topic in the literature. In fact, locating nonlinearities in mechanical systems turns out to be a challenging problem when treated nonparametrically, that is, without fitting a model. The present contribution takes a new look at this problem by exploiting some recent developments in the identification of dynamic networks, originating from the systems and control community.
Original languageEnglish
Title of host publicationNonlinear Dynamics, Volume 1
Subtitle of host publicationProceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018
EditorsGaetan Kerschen
PublisherSpringer
Pages363-367
Number of pages5
ISBN (Electronic)978-3-319-74280-9
ISBN (Print)978-3-319-74279-3
DOIs
Publication statusPublished - 7 Jun 2018
Event36th IMAC, A Conference and Exposition on Structural Dynamics, 2018 - Orlando, United States
Duration: 12 Feb 201815 Feb 2018

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series

Conference

Conference36th IMAC, A Conference and Exposition on Structural Dynamics, 2018
CountryUnited States
CityOrlando
Period12/02/1815/02/18

Keywords

  • Nonlinear structural dynamics
  • Nonlinear system identification
  • Nonlinearity location
  • Best linear approximation
  • Dynamic networks

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  • Cite this

    Noël, J. P., Schoukens, M., & Van Den Hof, P. M. J. (2018). Locating nonlinearity in mechanical systems: a dynamic network perspective. In G. Kerschen (Ed.), Nonlinear Dynamics, Volume 1: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018 (pp. 363-367). (Conference Proceedings of the Society for Experimental Mechanics Series). Springer. https://doi.org/10.1007/978-3-319-74280-9_38