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Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models

Auteur(s):




Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2020
Page(s): 1-12
DOI: 10.1155/2020/8712907
Abstrait:

In this article, an approach for using structural health monitoring coupled extreme stress data in dynamic extreme stress prediction of steel bridges is presented, where the coupled extreme stress data means the extreme stress data with dynamicity, randomness, and trend. Firstly, the modeling processes about dynamic coupled linear models (DCLM) are provided based on a supposed coupled time series; furthermore, the dynamic probabilistic recursion processes about DCLM are given with Bayes method; secondly, the monitoring dynamic coupled extreme stress data is taken as a time series, historical monitoring coupled extreme stress data-based DCLM and the corresponding Bayesian probabilistic recursion processes are given for predicting bridge extreme stresses; furthermore, the monitoring mechanism is provided for monitoring the prediction precision of DCLM; finally, the monitoring coupled extreme stress data of a steel bridge is used to illustrate the proposed approach which can provide the foundations for bridge reliability prediction and assessment.

Copyright: © 2020 Xueping Fan et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
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  • Reference-ID
    10429583
  • Publié(e) le:
    14.08.2020
  • Modifié(e) le:
    14.08.2020