Smart Structures and Systems

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Damage detection for decks of concrete girder bridges using the frequency obtained from an actively excited vehicle

  • Zhang, Jian (School of Civil Engineering, Dalian University of Technology) ;
  • Qu, Chun-Xu (School of Civil Engineering, Dalian University of Technology) ;
  • Yi, Ting-Hua (School of Civil Engineering, Dalian University of Technology) ;
  • Li, Hong-Nan (School of Civil Engineering, Dalian University of Technology)
  • Received : 2020.05.02
  • Accepted : 2020.11.12
  • Published : 2021.01.25
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Abstract

Concrete bridge decks may suffer local damage such as delamination, cracking, reinforcement corrosion and spalling during service. Visual inspection and nondestructive evaluation (NDE) technologies are extensively used for monitoring damage in bridge decks. This paper presents a damage detection method for decks of concrete girder bridges using the frequency obtained from an actively excited vehicle. First, the solution for the frequency of the deck with a concentrated mass is derived with Rayleigh's method, where the bridge deck is regarded as a slab supported on four sides, and the test vehicle is simplified as a concentrated mass. The validity of the proposed method that uses the frequency change to detect the local damage is verified. Then, the damage detection procedure for bridge decks is proposed, and the numerical analysis is performed on a typical concrete girder bridge to prove the validity of the method. Finally, the damage detection experiment for the plywood plate verifies the effectiveness of the proposed method. The results of this study provide an effective method for detecting damage in the decks of concrete girder bridges, which is time-saving and easier to implement.

Keywords

Acknowledgement

This research work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 51625802, 51978128, 51778105), the LiaoNing Revitalization Talents Program (Grant No. XLYC1802035), and the Foundation for High Level Talent Innovation Support Program of Dalian (Grant No. 2017RD03).

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