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author:

Han, Jian-Gang (Han, Jian-Gang.) [1] | Ren, Wei-Xin (Ren, Wei-Xin.) [2] | Xu, Xiao-Xia (Xu, Xiao-Xia.) [3]

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EI Scopus

Abstract:

The structural operating conditions may significantly differ from those applied during laboratory tests where the structure is well known, well installed and properly excited. For structures under their natural loading conditions, or excited by random forces, excitations cannot be measured and are usually non stationary. Hence, an improvement operational modal analysis is a useful complement to the traditional modal analysis approach. The aim of this paper is to present the application of a new identification procedure, named wavelet-based identification technique of structural modal parameters. The wavelet-based identification that works in the time-frequency domain is used to identify the dynamic characteristics of the structural system in terms of natural frequencies, damping coefficients and mode shape. The paper has shown how the amplitude and the phase of the wavelet transform of operational vibration measurements are related to eigenfrequencies and damping coefficients, and the wavelet-based spectrum analysis is used to identify the mode shapes of the structure. A simulation example has demonstrated that the current identified results are comparable with those previously obtained from the peak pick method in frequency domain and stochastic subspace identification in time domain.

Keyword:

Damping Frequency domain analysis Modal analysis Parameter estimation Spectrum analysis Stochastic systems Structural analysis Time domain analysis Vibration analysis Wavelet transforms

Community:

  • [ 1 ] [Han, Jian-Gang]Department of Civil Engineering, Fuzhou University, China
  • [ 2 ] [Ren, Wei-Xin]Department of Civil Engineering, Fuzhou University, China
  • [ 3 ] [Xu, Xiao-Xia]Department of Civil Engineering, Fuzhou University, China

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Year: 2005

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

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