دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Feature-constrained automatic geometric deformation analysis method of bridge models toward digital twin
المؤلفون: Jun Zhu, Niya Luo, Zhihao Guo, Jianbo Lai, Li Zuo, Chuanjun Zhang, Yukun Guo, Ya Hu
المصدر: International Journal of Digital Earth, Vol 17, Iss 1 (2024)
بيانات النشر: Taylor & Francis Group, 2024.
سنة النشر: 2024
المجموعة: LCC:Mathematical geography. Cartography
مصطلحات موضوعية: Feature-constrained, bridge digital twins, geometric deformation, automatic diagnostic analysis, improved Hausdorff algorithm, Mathematical geography. Cartography, GA1-1776
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 17538947
1753-8955
1753-8947
العلاقة: https://doaj.org/toc/1753-8947Test; https://doaj.org/toc/1753-8955Test
DOI: 10.1080/17538947.2024.2312219
الوصول الحر: https://doaj.org/article/d091bcf5d91e4d409816aacbb89ec3a7Test
رقم الانضمام: edsdoj.091bcf5d91e4d409816aacbb89ec3a7
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17538947
17538955
DOI:10.1080/17538947.2024.2312219