scholarly journals Reconstruction of Governing Equations from Vibration Measurements for Geometrically Nonlinear Systems

Lubricants ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 64 ◽  
Author(s):  
Marco Didonna ◽  
Merten Stender ◽  
Antonio Papangelo ◽  
Filipe Fontanela ◽  
Michele Ciavarella ◽  
...  

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.

2021 ◽  
Vol 54 (7) ◽  
pp. 162-167
Author(s):  
Ştefan-Cristian Nechita ◽  
Roland Tóth ◽  
Koos van Berkel

Author(s):  
Jaewon Choi ◽  
Mohsen Nakhaeinejad ◽  
Michael D. Bryant

This study illustrates a data driven system identification method for loudspeaker model estimation using the knowledge of the underlying physics of loudspeakers. In this study, diaphragm displacement is analyzed to estimate the model structure and parameters based on impulse response equivalent sampling and autoregressive moving average model. The estimated loudspeaker models are compared in the frequency response function plot. It is shown that the autoregressive moving average (ARMA) based loudspeaker models are comparable to the model estimated by the conventional method based on electrical impedance. Also ARMA modeling strategies with and without knowledge of the physics-based model are compared. Some issues related to ARMA modeling are addressed.


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