Smart Structures and Systems

  • 제15권2호
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  • Pages.395-408
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  • 2015
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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A Bayesian approach for vibration-based long-term bridge monitoring to consider environmental and operational changes

  • Kim, Chul-Woo (Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto University) ;
  • Morita, Tomoaki (Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto University) ;
  • Oshima, Yoshinobu (Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto University) ;
  • Sugiura, Kunitomo (Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto University)
  • 투고 : 2014.12.05
  • 심사 : 2015.01.11
  • 발행 : 2015.02.25
⟨ 이전 논문 다음 논문 ⟩

초록

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

키워드

과제정보

연구 과제 주관 기관 : JSPS

참고문헌

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피인용 문헌

  1. Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges 2017, https://doi.org/10.1177/1475921717721137
  2. Automated, strain-based, output-only bridge damage detection pp.2190-5479, 2018, https://doi.org/10.1007/s13349-018-0311-6
  3. Long-term bridge health monitoring and performance assessment based on a Bayesian approach vol.14, pp.7, 2018, https://doi.org/10.1080/15732479.2018.1436572