International Journal of Digital Earth (Dec 2024)

Feature-constrained automatic geometric deformation analysis method of bridge models toward digital twin

  • Jun Zhu,
  • Niya Luo,
  • Zhihao Guo,
  • Jianbo Lai,
  • Li Zuo,
  • Chuanjun Zhang,
  • Yukun Guo,
  • Ya Hu

DOI
https://doi.org/10.1080/17538947.2024.2312219
Journal volume & issue
Vol. 17, no. 1

Abstract

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ABSTRACTIt is very important to construct digital twin scenes, which can accurately describe the dynamically changing geographical environment and improve the level of refined management in bridge construction. This article proposes a feature constrained automatic diagnostic analysis method for geometric deformation of bridge digital twins. The geometric deformation feature library of bridge twins was first created to accurately describe structural relationships and behavior characteristics. Secondly, line surface feature constraints were used to extract geometric deformation information from bridge digital twins. Then, a geometric deformation diagnosis algorithm was designed based on an improved Hausdorff method. Finally, a case study was conducted to implement experimental analysis. The experimental results show that the method proposed in this paper can automatically extract the geometric morphology and rapidly calculate line and surface deformations for point cloud bridge digital twins. It achieves an efficiency improvement above 90% and with millimeter-level accuracy, which effectively enhances the diagnostic analysis capabilities for geographical digital twin models.

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