Modal identification from nonstationary ambient vibration data using improved Random Decrement Technique

Dar-Yun Chiang, Chang Sheng Lin, Ho Hun Chen

Research output: Contribution to journalArticle

Abstract

An effective identification method is developed for determining the modal parameters of a structure from its measured nonstationary ambient vibration data. The conventional Random Decrement Technique (RDD) is applicable to linear systems excited by stationary white inputs only, and its effectiveness is usually limited by the length of measurement records available. It is shown that if the ambient excitation can be modeled as a zero-mean nonstationary process, then the nonstationary cross random decrement signatures of structural response are in the same mathematical form as that of free vibration of the structure, from which modal parameters of a system can then be identified. To improve the accuracy of identification, a modification of the sampling procedure in RDD is presented such that more response samples can be obtained to perforin averaging analysis. Numerical simulations confirm the validity of the proposed modal-identification method from nonstationary ambient response data.

Original languageEnglish
Pages (from-to)67-74
Number of pages8
JournalHangkong Taikong ji Minhang Xuekan/Journal of Aeronautics, Astronautics and Aviation, Series B
Volume44
Issue number2
DOIs
Publication statusPublished - 2012 Oct 1

Fingerprint

identification method
Linear systems
vibration
Sampling
structural response
Computer simulation
free vibration
linear systems
sampling
signatures
simulation
excitation
parameter
analysis

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

Cite this

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abstract = "An effective identification method is developed for determining the modal parameters of a structure from its measured nonstationary ambient vibration data. The conventional Random Decrement Technique (RDD) is applicable to linear systems excited by stationary white inputs only, and its effectiveness is usually limited by the length of measurement records available. It is shown that if the ambient excitation can be modeled as a zero-mean nonstationary process, then the nonstationary cross random decrement signatures of structural response are in the same mathematical form as that of free vibration of the structure, from which modal parameters of a system can then be identified. To improve the accuracy of identification, a modification of the sampling procedure in RDD is presented such that more response samples can be obtained to perforin averaging analysis. Numerical simulations confirm the validity of the proposed modal-identification method from nonstationary ambient response data.",
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