@inproceedings{12d8025ca1094e67896d4c38a655c93c,
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",
author = "J.P. No{\"e}l and M. Schoukens and {Van Den Hof}, P.M.J.",
year = "2019",
doi = "10.1007/978-3-319-74280-9_38",
language = "English",
isbn = "978-3-319-74279-3",
series = "Conference Proceedings of the Society for Experimental Mechanics Series",
publisher = "Springer",
pages = "363--367",
editor = "Gaetan Kerschen",
booktitle = "Nonlinear Dynamics, Volume 1",
address = "Germany",
note = "36th IMAC, A Conference and Exposition on Structural Dynamics, 2018 ; Conference date: 12-02-2018 Through 15-02-2018",
}