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

Authors :
Jun Zhu
Niya Luo
Zhihao Guo
Jianbo Lai
Li Zuo
Chuanjun Zhang
Yukun Guo
Ya Hu
Source :
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Publication Year :
2024
Publisher :
Taylor & Francis Group, 2024.

Abstract

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.

Details

Language :
English
ISSN :
17538947 and 17538955
Volume :
17
Issue :
1
Database :
Directory of Open Access Journals
Journal :
International Journal of Digital Earth
Publication Type :
Academic Journal
Accession number :
edsdoj.091bcf5d91e4d409816aacbb89ec3a7
Document Type :
article
Full Text :
https://doi.org/10.1080/17538947.2024.2312219