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Reconstruction of governing equations from vibration measurements for geometrically nonlinear systems
Citation Link: https://doi.org/10.15480/882.2375
Publikationstyp
Journal Article
Date Issued
2019-08-05
Sprache
English
Author(s)
Papangelo, Antonio
Institut
TORE-DOI
TORE-URI
Journal
Volume
7
Issue
8
Article Number
64
Citation
Lubricants 7 (8): 64 (2019)
Publisher DOI
Scopus ID
Publisher
Multidisciplinary Digital Publishing Institute
Data-driven system identification procedures have recently enabled the reconstruction of governing differential equations from vibration signal recordings. In this contribution, the sparse identification of nonlinear dynamics is applied to structural dynamics of a geometrically nonlinear system. First, the methodology is validated against the forced Duffing oscillator to evaluate its robustness against noise and limited data. Then, differential equations governing the dynamics of two weakly coupled cantilever beams with base excitation are reconstructed from experimental data. Results indicate the appealing abilities of data-driven system identification: underlying equations are successfully reconstructed and (non-)linear dynamic terms are identified for two experimental setups which are comprised of a quasi-linear system and a system with impacts to replicate a piecewise hardening behavior, as commonly observed in contacts.
Subjects
nonlinear dynamics
system identification
sparse regression
time series
geometric nonlinearity
contact
DDC Class
620: Ingenieurwissenschaften
More Funding Information
Deutsche Forschungsgemeinschaft
Italian Ministry of Education, University and
Research (MIUR)
Research (MIUR)
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