Nonlinear MDOF system characterization and identification using the Hilbert-Huang transform

G. Kerschen, A. F. Vakakis, Y. S. Lee, D. M. Mcfarland, Lawrence Bergman

Research output: Contribution to conferencePaperpeer-review

Abstract

The Hilbert transform is one of the most successful approaches to tracking the varying nature of vibration of a large class of nonlinear systems thanks to the extraction of backbone curves from experimental data. Because signals with multiple frequency components do not admit a well-behaved Hilbert transform, it is inherently limited to the analysis of single-degree-of-freedom systems. In this study, the joint application of the complexification-averaging method and the empirical mode decomposition enables us to develop a new technique, the slow-flow model identification method. Through numerical and experimental applications, we demonstrate that the proposed method is adequate for characterizing and identifying multi-degree-offreedom nonlinear systems.

Original languageEnglish (US)
Pages2735-2750
Number of pages16
StatePublished - 2006
Externally publishedYes
EventInternational Conference on Noise and Vibration Engineering 2006, ISMA 2006 - Heverlee, Belgium
Duration: Sep 18 2006Sep 20 2006

Other

OtherInternational Conference on Noise and Vibration Engineering 2006, ISMA 2006
Country/TerritoryBelgium
CityHeverlee
Period9/18/069/20/06

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Materials Science(all)
  • Acoustics and Ultrasonics
  • Condensed Matter Physics

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