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

G. Kerschen, Alexander F Vakakis, Y. S. Lee, D. M. McFarland, Lawrence Bergman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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, this transform is inherently limited to the analysis of single-degree-of-freedom systems; this shortcoming is potentially overcome by the Hilbert-Huang transform (HHT). In this study, the joint application of the complexification-averaging method and the HHT enables us to develop a new technique, the slow-flow model identification method. Through an experimental application, we demonstrate that the proposed method is adequate for characterizing and identifying multi-degree-of-freedom nonlinear systems.

Original languageEnglish (US)
Title of host publicationIMAC-XXV - Celebrating 25 Years of IMAC
StatePublished - Dec 1 2007
Event25th Conference and Exposition on Structural Dynamics 2007, IMAC-XXV - Orlando, FL, United States
Duration: Feb 19 2007Feb 22 2007

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series
ISSN (Print)2191-5644
ISSN (Electronic)2191-5652

Other

Other25th Conference and Exposition on Structural Dynamics 2007, IMAC-XXV
CountryUnited States
CityOrlando, FL
Period2/19/072/22/07

ASJC Scopus subject areas

  • Engineering(all)
  • Computational Mechanics
  • Mechanical Engineering

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