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Smart Structures and Systems
  Volume 26, Number 1, July 2020, pages 11-21
DOI: http://dx.doi.org/10.12989/sss.2020.26.1.011
 


Cloud monitoring system for assembled beam bridge based on index of dynamic strain correlation coefficient
Yiming Zhao, Danhui Dan, Xingfei Yan and Kailong Zhang

 
Abstract
    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.
 
Key Words
    cloud monitoring and diagnosis system; assembled beam bridge; dynamic strain; correlation coefficient; lateral collaborative working performance
 
Address
(1) Yiming Zhao, Danhui Dan:
School of Civil Engineering, Tongji University, 1239 Siping Road, Shanghai, 200092, China;
(2) Danhui Dan:
Key Laboratory of Performance Evolution and Control for Engineering Structures of Ministry of Education, Tongji University, 1239 Siping Road, Shanghai, 200092, China;
(3) Yiming Zhao:
Shanghai Construction Group, Engineering General Institute, Shanghai, 201114, China;
(4) Xingfei Yan, Kailong Zhang:
Shanghai Urban Construction Design Research Institute, Shanghai, 200125, China.
 

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