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

ABSTRACT

It 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.

KEYWORDS:

• Feature-constrained
• bridge digital twins
• geometric deformation
• automatic diagnostic analysis
• improved Hausdorff algorithm

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by National Natural Science Foundation of China (Grant Nos. U2034202, 42271424 and 42171397) and Technology research and development plan project of Xi'an-Chengdu passenger dedicated line Shaanxi Co., Ltd. (Xikang High Speed Rail Contract (2021) No. 24).