Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale Algorithms Article Swipe
Dongmei Tan
,
Li Wan
,
Tao Yu
,
Baifeng Ji
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25133869
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25133869
To address the inefficiencies and limited spatial resolution of traditional single-point monitoring techniques, this study proposes a multi-scale analysis method that integrates the Multi-Scale Model-to-Model Cloud Comparison (M3C2) algorithm with least-squares plane fitting. This approach employs the M3C2 algorithm for qualitative full-field deformation detection and utilizes least-squares plane fitting for quantitative feature extraction. When applied to the approach span of a cross-river bridge in Hubei Province, China, this method leverages dense point clouds (greater than 500 points per square meter) acquired using a Leica RTC360 scanner. Data preprocessing incorporates curvature-adaptive cascade denoising, achieving over 98% noise removal while retaining more than 95% of structural features, along with octree-based simplification. By extracting multi-level slice features from bridge decks and piers, this method enables the simultaneous analysis of global trends and local deformations. The results revealed significant deformation, with an average settlement of 8.2 mm in the left deck area. The bridge deck exhibited a deformation trend characterized by left and higher right in the vertical direction, while the bridge piers displayed noticeable tilting, particularly with the maximum offset of the rear pier columns reaching 182.2 mm, which exceeded the deformation of the front pier. The bridge deck’s micro-settlement error was ±1.2 mm, and the pier inclination error was ±2.8 mm, meeting the Chinese Highway Bridge Maintenance Code (JTG H11-2004) and the American Association of State Highway and Transportation Officials (AASHTO) standards, and the multi-scale algorithm achieved engineering-level accuracy. Utilizing point cloud densities >500 pt/m2, the M3C2 algorithm achieved a spatial resolution of 0.5 mm, enabling sub-millimeter full-field analysis for complex scenarios. This method significantly enhances bridge safety monitoring precision, enhances the precision of intelligent systems monitoring, and supports the development of targeted systems as pile foundation reinforcement efforts and as improvements to foundations.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s25133869
- https://www.mdpi.com/1424-8220/25/13/3869/pdf?version=1750497428
- OA Status
- gold
- Cited By
- 1
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411568715
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411568715Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/s25133869Digital Object Identifier
- Title
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Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale AlgorithmsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-21Full publication date if available
- Authors
-
Dongmei Tan, Li Wan, Tao Yu, Baifeng JiList of authors in order
- Landing page
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https://doi.org/10.3390/s25133869Publisher landing page
- PDF URL
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https://www.mdpi.com/1424-8220/25/13/3869/pdf?version=1750497428Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/1424-8220/25/13/3869/pdf?version=1750497428Direct OA link when available
- Concepts
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Deformation monitoring, Bridge (graph theory), Laser scanning, Deformation (meteorology), Scale (ratio), Structural engineering, Computer science, Algorithm, Laser, Engineering, Materials science, Optics, Composite material, Physics, Medicine, Internal medicine, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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46Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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