Abstract
Modal analysis is a well-established method for analysis of linear dynamic structures, but its extension to non-linear structures has proven to be much more problematic. A number of viewpoints on non-linear modal analysis as well as a range of different non-linear system identification techniques have emerged in the past, each of which tries to preserve a subset of properties of the original linear theory. The objective of this paper is to discuss how the Hilbert-Huang transform can be used for detection and characterization of non-linearity, and to present an optimization framework which combines the Hilbert-Huang transform and complex non-linear modal analysis for quantification of the selected model. It is argued that the complex non-linear modes relate to the intrinsic mode functions through the reduced order model of slow-flow dynamics. The method is demonstrated on simulated data from a system with cubic non-linearity.
| Original language | English |
|---|---|
| Title of host publication | Nonlinear Dynamics, Volume 1: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics 2017 |
| Editors | Gaetan Kerschen |
| Place of Publication | Cham |
| Publisher | Springer International Publishing AG |
| Pages | 77-86 |
| Number of pages | 10 |
| ISBN (Print) | 978-3-319-54404-5 |
| DOIs | |
| Publication status | Published - 2017 |
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