Smart Structures and Systems

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A fast and simplified crack width quantification method via deep Q learning

  • Xiong Peng (Hunan University of Science and Technology) ;
  • Kun Zhou (Hunan University of Science and Technology) ;
  • Bingxu Duan (Hunan University of Science and Technology) ;
  • Xingu Zhong (Hunan University of Science and Technology) ;
  • Chao Zhao (Hunan University of Science and Technology) ;
  • Tianyu Zhang (Hunan University of Science and Technology)
  • Received : 2022.05.13
  • Accepted : 2023.09.26
  • Published : 2023.10.25
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Abstract

Crack width is an important indicator to evaluate the health condition of the concrete structure. The crack width is measured by manual using crack width gauge commonly, which is time-consuming and laborious. In this paper, we have proposed a fast and simplified crack width quantification method via deep Q learning and geometric calculation. Firstly, the crack edge is extracted by using U-Net network and edge detection operator. Then, the intelligent decision of is made by the deep Q learning model. Further, the geometric calculation method based on endpoint and curvature extreme point detection is proposed. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method, achieving high precision in the real crack width quantification.

Keywords

Acknowledgement

This study is supported by National Natural Science Foundation of China (Grant No. 51678235) and the Natural Science Foundation of Hunan Province (2020JJ5195), to which the authors are grateful.

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