Smart Structures and Systems

  • 제17권3호
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  • Pages.391-411
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  • 2016
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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

Mode identifiability of a multi-span cable-stayed bridge utilizing stabilization diagram and singular values

  • Goi, Y. (Department of Civil and Earth Resources Engineering, Kyoto University) ;
  • Kim, C.W. (Department of Civil and Earth Resources Engineering, Kyoto University)
  • 투고 : 2015.06.17
  • 심사 : 2015.11.12
  • 발행 : 2016.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

This study investigates the mode identifiability of a multi-span cable-stayed bridge in terms of a benchmark study using stabilization diagrams of a system model identified using stochastic subspace identification (SSI). Cumulative contribution ratios (CCRs) estimated from singular values of system models under different wind conditions were also considered. Observations revealed that wind speed might influence the mode identifiability of a specific mode of a cable-stayed bridge. Moreover the cumulative contribution ratio showed that the time histories monitored during strong winds, such as those of a typhoon, can be modeled with less system order than under weak winds. The blind data Acc 1 and Acc 2 were categorized as data obtained under a typhoon. Blind data Acc 3 and Acc 4 were categorized as data obtained under wind conditions of critical wind speeds around 7.5 m/s. Finally, blind data Acc 5 and Acc 6 were categorized as data measured under weak wind conditions.

키워드

참고문헌

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피인용 문헌

  1. Investigation of Operational Modal Identification of a Cable-Stayed Bridge Based on Bayesian Estimation Considering Stochastic Uncertainty vol.72, pp.2, 2016, https://doi.org/10.2208/jscejam.72.I_751
  2. Mode identifiability of a cable-stayed bridge using modal contribution index vol.20, pp.2, 2017, https://doi.org/10.12989/sss.2017.20.2.115
  3. Modal flexibility based damage detection for suspension bridge hangers: A numerical and experimental investigation vol.23, pp.1, 2016, https://doi.org/10.12989/sss.2019.23.1.015
  4. Automatic identification of modal parameters for structures based on an uncertainty diagram and a convolutional neural network vol.28, pp.None, 2016, https://doi.org/10.1016/j.istruc.2020.08.077
  5. Application of short-time stochastic subspace identification to estimate bridge frequencies from a traversing vehicle vol.230, pp.None, 2016, https://doi.org/10.1016/j.engstruct.2020.111688