Smart Structures and Systems

  • 제30권3호
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  • Pages.263-271
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  • 2022
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

On the development of data-based damage diagnosis algorithms for structural health monitoring

  • Kiremidjian, Anne S. (Department of Civil and Environmental Engineering, Stanford University)
  • 투고 : 2022.06.12
  • 심사 : 2022.07.17
  • 발행 : 2022.09.25
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper we present an overview of damage diagnosis algorithms that have been developed over the past two decades using vibration signals obtained from structures. Then, the paper focuses primarily on algorithms that can be used following an extreme event such as a large earthquake to identify structural damage for responding in a timely manner. The algorithms presented in the paper use measurements obtained from accelerometers and gyroscope to identify the occurrence of damage and classify the damage. Example algorithms are presented include those based on autoregressive moving average (ARMA), wavelet energies from wavelet transform and rotation models. The algorithms are illustrated through application of data from test structures such as the ASCE Benchmark structure and laboratory tests of scaled bridge columns and steel frames. The paper concludes by identifying needs for research and development in order for such algorithms to become viable in practice.

키워드

과제정보

The research described in this paper was financially supported by the Natural Science Foundation, the John A Blume Earthquake Engineering Center, and the John Blume and James Gere Fellowships at Stanford University. The author gratefully acknowledges the contribution of the doctoral students involved in the research - Krishnan Nair, Pooya Sarabandi, Alan Cheung, Hae-Young Noh, Konstantinos Balafas, and Yezheng Liao. In addition, the help of colleagues who enabled us to participate in various laboratory tests or provided key data for testing the algorithms is greatly appreciated. They include Professor Emeritus Seiid Seiidi of the University of Nevada, Reno, the late Professor Steve Mahin of the University of California, Berkeley, and Professor Emeritus H.C. Loh of the National Taiwan University.

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