A displacement measurement methodology for deformation monitoring of long‐span arch bridges during construction based on scalable multi‐camera system

This study presents a scalable multi-camera system (S-MCS) for high-precision displacement measurement and deformation monitoring of long-span arch bridges during construction. Traditional methods such as robotic total stations (RTS) and single-camera systems face limitations in dynamic scalability, synchronous multi-point monitoring, and robustness against environmental disturbances. To address these challenges, the proposed S-MCS integrates dynamically expandable measuring cameras and dual correcting cameras to compensate for platform ego-motion. A self-calibration algorithm and spatiotemporal reference alignment framework are developed to ensure measurement consistency across evolving construction phases. The system was deployed on a 600-m-span arch bridge, achieving sub-millimeter accuracy (root mean square error ≤ 1.09 mm) validated against RTS data. Key innovations include real-time platform motion compensation, adaptive coverage expansion, and high-frequency sampling for capturing transient structural responses. Comparative analyses under construction loads, thermal variations, and extreme crosswinds demonstrated the system's superiority in tracking multi-point displacements, resolving dynamic behaviors and supporting safety assessments. The S-MCS provides a robust solution for automated, large-scale structural health monitoring, with potential applications in diverse infrastructure projects requiring adaptive, high-resolution deformation tracking.

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Publication Details

Journal
Computer-Aided Civil and Infrastructure Engineering
Published
2025-04-05
DOI
https://doi.org/10.1111/mice.13475
Citations
5
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
4.77

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article

A displacement measurement methodology for deformation monitoring of long‐span arch bridges during construction based on scalable multi‐camera system

Danyang Ma, Yihe Yin, Xiaohua Ding, Wenjun Chen et al.
5 citations
Computer-Aided Civil and Infrastructure Engineering
Structural Health Monitoring Techniques
4.77
article

A displacement measurement methodology for deformation monitoring of long‐span arch bridges during construction based on scalable multi‐camera system

Danyang Ma, Yihe Yin, Xiaohua Ding, Wenjun Chen, Xiaolin Liu, Biao Hu, Lin‐Hai Han, Xiao Guo, Qifeng Yu
article en
5 citations

Abstract

This study presents a scalable multi-camera system (S-MCS) for high-precision displacement measurement and deformation monitoring of long-span arch bridges during construction. Traditional methods such as robotic total stations (RTS) and single-camera systems face limitations in dynamic scalability, synchronous multi-point monitoring, and robustness against environmental disturbances. To address these challenges, the proposed S-MCS integrates dynamically expandable measuring cameras and dual correcting cameras to compensate for platform ego-motion. A self-calibration algorithm and spatiotemporal reference alignment framework are developed to ensure measurement consistency across evolving construction phases. The system was deployed on a 600-m-span arch bridge, achieving sub-millimeter accuracy (root mean square error ≤ 1.09 mm) validated against RTS data. Key innovations include real-time platform motion compensation, adaptive coverage expansion, and high-frequency sampling for capturing transient structural responses. Comparative analyses under construction loads, thermal variations, and extreme crosswinds demonstrated the system's superiority in tracking multi-point displacements, resolving dynamic behaviors and supporting safety assessments. The S-MCS provides a robust solution for automated, large-scale structural health monitoring, with potential applications in diverse infrastructure projects requiring adaptive, high-resolution deformation tracking.

Computer-Aided Civil and Infrastructure EngineeringVol. 40(13)
Guangxi University (CN), Shenzhen University (CN), Beihang University (CN)
China Postdoctoral Science Foundation, National Key Research and Development Program of China
Openalex Percentile: Top 6%
Structural Health Monitoring Techniques
4.77
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