Structural Monitoring and Maintenance

  • 제9권2호
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  • Pages.107-127
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  • 2022
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  • 2288-6605(pISSN)
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  • 2288-6613(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Damage evaluation of seismic response of structure through time-frequency analysis technique

  • Chen, Wen-Hui (P-Waver Inc.) ;
  • Hseuh, Wen (Department of Civil Engineering, National Taiwan University) ;
  • Loh, Kenneth J. (Department of Structural Engineering, University of California-San Diego) ;
  • Loh, Chin-Hsiung (Department of Civil Engineering, National Taiwan University)
  • 투고 : 2020.05.17
  • 심사 : 2022.03.31
  • 발행 : 2022.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

Structural health monitoring (SHM) has been related to damage identification with either operational loads or other environmental loading playing a significant complimentary role in terms of structural safety. In this study, a non-parametric method of time frequency analysis on the measurement is used to address the time-frequency representation for modal parameter estimation and system damage identification of structure. The method employs the wavelet decomposition of dynamic data by using the modified complex Morlet wavelet with variable central frequency (MCMW+VCF). Through detail discussion on the selection of model parameter in wavelet analysis, the method is applied to study the dynamic response of both steel structure and reinforced concrete frame under white noise excitation as well as earthquake excitation from shaking table test. Application of the method to building earthquake response measurement is also examined. It is shown that by using the spectrogram generated from MCMW+VCF method, with suitable selected model parameter, one can clearly identify the time-varying modal frequency of the reinforced concrete structure under earthquake excitation. Discussions on the advantages and disadvantages of the method through field experiments are also presented.

키워드

과제정보

This research was supported by the U.S. Department of Conservation for the California Strong Motion Instrumentation Program (CSMIP) data interpretation project no. 1018-567.

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