Locating nonlinearity in mechanical systems: a dynamic network perspective

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

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.
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
ISBN (Electronic)978-3-319-74280-9
ISBN (Print)978-3-319-74279-3
DOIs
StatePublished - 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

Fingerprint

Network dynamics
Nonlinearity

Keywords

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

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. DOI: 10.1007/978-3-319-74280-9_38
Noël, J.P. ; Schoukens, M. ; Van Den Hof, P.M.J./ Locating nonlinearity in mechanical systems: a dynamic network perspective. Nonlinear Dynamics, Volume 1: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018. editor / Gaetan Kerschen. Springer, 2018. pp. 363-367 (Conference Proceedings of the Society for Experimental Mechanics Series).
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title = "Locating nonlinearity in mechanical systems: a dynamic network perspective",
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.",
keywords = "Nonlinear structural dynamics, Nonlinear system identification, Nonlinearity location, Best linear approximation, Dynamic networks",
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Noël, JP, Schoukens, M & Van Den Hof, PMJ 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. Conference Proceedings of the Society for Experimental Mechanics Series, Springer, pp. 363-367, 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, Orlando, United States, 12/02/18. DOI: 10.1007/978-3-319-74280-9_38

Locating nonlinearity in mechanical systems: a dynamic network perspective. / Noël, J.P.; Schoukens, M.; Van Den Hof, P.M.J.

Nonlinear Dynamics, Volume 1: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018. ed. / Gaetan Kerschen. Springer, 2018. p. 363-367 (Conference Proceedings of the Society for Experimental Mechanics Series).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

TY - GEN

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AB - 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.

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Noël JP, Schoukens M, Van Den Hof PMJ. Locating nonlinearity in mechanical systems: a dynamic network perspective. In Kerschen G, editor, Nonlinear Dynamics, Volume 1: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018. Springer. 2018. p. 363-367. (Conference Proceedings of the Society for Experimental Mechanics Series). Available from, DOI: 10.1007/978-3-319-74280-9_38