Smart Structures and Systems

  • 제16권1호
  • /
  • Pages.163-181
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  • 2015
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Overall damage identification of flag-shaped hysteresis systems under seismic excitation

  • Zhou, Cong (Department of Mechanical Engineering, University of Canterbury) ;
  • Chase, J. Geoffrey (Department of Mechanical Engineering, University of Canterbury) ;
  • Rodgers, Geoffrey W. (Department of Mechanical Engineering, University of Canterbury) ;
  • Xu, Chao (School of Astronautics, Northwestern Polytechnical University) ;
  • Tomlinson, Hamish (Department of Mechanical Engineering, University of Canterbury)
  • 투고 : 2014.04.13
  • 심사 : 2014.11.01
  • 발행 : 2015.07.25
⟨ 이전 논문 다음 논문 ⟩

초록

This research investigates the structural health monitoring of nonlinear structures after a major seismic event. It considers the identification of flag-shaped or pinched hysteresis behavior in response to structures as a more general case of a normal hysteresis curve without pinching. The method is based on the overall least squares methods and the log likelihood ratio test. In particular, the structural response is divided into different loading and unloading sub-half cycles. The overall least squares analysis is first implemented to obtain the minimum residual mean square estimates of structural parameters for each sub-half cycle with the number of segments assumed. The log likelihood ratio test is used to assess the likelihood of these nonlinear segments being true representations in the presence of noise and model error. The resulting regression coefficients for identified segmented regression models are finally used to obtain stiffness, yielding deformation and energy dissipation parameters. The performance of the method is illustrated using a single degree of freedom system and a suite of 20 earthquake records. RMS noise of 5%, 10%, 15% and 20% is added to the response data to assess the robustness of the identification routine. The proposed method is computationally efficient and accurate in identifying the damage parameters within 10% average of the known values even with 20% added noise. The method requires no user input and could thus be automated and performed in real-time for each sub-half cycle, with results available effectively immediately after an event as well as during an event, if required.

키워드

과제정보

연구 과제 주관 기관 : China Scholarship Council, University of Canterbury

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