Smart Structures and Systems

  • 제26권1호
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  • Pages.11-21
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  • 2020
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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Cloud monitoring system for assembled beam bridge based on index of dynamic strain correlation coefficient

  • Zhao, Yiming (School of Civil Engineering, Tongji University) ;
  • Dan, Danhui (School of Civil Engineering, Tongji University) ;
  • Yan, Xingfei (Shanghai Urban Construction Design Research Institute) ;
  • Zhang, Kailong (Shanghai Urban Construction Design Research Institute)
  • 투고 : 2019.08.31
  • 심사 : 2020.04.20
  • 발행 : 2020.07.25
⟨ 이전 논문 다음 논문 ⟩

초록

The hinge joint is the key to the overall cooperative working performance of the assembled beam bridge, and it is also the weakest part during the service period. This paper proposes a method for monitoring and evaluating the lateral cooperative working performance of fabricated beam bridges based on dynamic strain correlation coefficient indicator. This method is suitable for monitoring and evaluation of hinge joints status between prefabricated girders and overall cooperative working performance of bridge, without interruption of traffic and easy implementation. The remote cloud monitoring and diagnosis system was designed and implemented on a real assembled beam bridge. The algorithms of data preprocessing, online indicator extraction and status diagnosis were given, and the corresponding software platform and scientific computing environment for cloud operation were developed. Through the analysis of real bridge monitoring data, the effectiveness and accuracy of the method are proved and it can be used in the health monitoring system of such bridges.

키워드

과제정보

This study is funded by the Opening Project of National Key Laboratory for Bridge Structural Health and Safety (BHSKL18-05-GF), National Natural Science Foundation of China (51878490); the National Key R&D Program of China (2017YFF0205605); Shanghai Urban Construction Design Research Institute Project ‘Bridge Safe Operation Big Data Acquisition Technology and Structure Monitoring System Research.

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