Multipoint dynamic displacement monitoring of long-span beam bridges and their time-space evolution using a camera-chain system

Deflection and lateral displacement are critical factors in bridge structural health monitoring. Vision-based displacement monitoring techniques have advantages, such as full-field coverage, high precision, real-time feedback, and automation. However, existing methods still face two key problems that limit their field application: a) an inherent trade-off between measurement range and accuracy, and b) the effect of environmental disturbance on observation platform stability. This paper proposes a camera-chain-based multipoint displacement measurement system for long-span beam bridges. The system primarily consists of double-head camera stations linked by artificial markers. By connecting the optical paths of the camera stations in the physical setup and compensating for motion-induced errors in the measurement model, the system can be deployed along a deformed beam to enable synchronized dynamic measurements at multiple points. Comparative field tests demonstrate that the displacement measurements obtained from this system are consistent with those from traditional methods, such as manual leveling and automated connecting pipe systems, while providing advantages in terms of dynamic monitoring and the breadth of measurement parameters. Benefiting from real-time multipoint measurement, the system captures detailed spatial deformation curves. In addition, the observed vehicle-induced evolution of bridge deflection aligns well with the recorded vehicle speed and can be used to evaluate the modal parameters of beam bridges. The proposed method and system can provide new options and better data for bridge displacement monitoring to support the accuracy and timeliness of safety warnings. • A linear camera-chain measurement model derived from a pinhole imaging model is presented. • A follow-up visual measurement system is proposed that can be placed on deformable bridges. • Existing methods are compared with the proposed model for long-term successful verification. • Dynamic displacement time-space evolutions are discussed based on the all-span multipoint observations.

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Publication Details

Journal
Computers in Industry
Published
2025-02-28
DOI
https://doi.org/10.1016/j.compind.2025.104271
Citations
1
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.95
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Multipoint dynamic displacement monitoring of long-span beam bridges and their time-space evolution using a camera-chain system

Biao Hu, Yihe Yin, Wenjun Chen, Xiaohua Ding et al.
1 citations
Computers in Industry
Structural Health Monitoring Techniques
0.95
article

Multipoint dynamic displacement monitoring of long-span beam bridges and their time-space evolution using a camera-chain system

Biao Hu, Yihe Yin, Wenjun Chen, Xiaohua Ding, Xiaolin Liu, Yueqiang Zhang, Zhendong Ge, Qifeng Yu
article en
1 citations

Abstract

Deflection and lateral displacement are critical factors in bridge structural health monitoring. Vision-based displacement monitoring techniques have advantages, such as full-field coverage, high precision, real-time feedback, and automation. However, existing methods still face two key problems that limit their field application: a) an inherent trade-off between measurement range and accuracy, and b) the effect of environmental disturbance on observation platform stability. This paper proposes a camera-chain-based multipoint displacement measurement system for long-span beam bridges. The system primarily consists of double-head camera stations linked by artificial markers. By connecting the optical paths of the camera stations in the physical setup and compensating for motion-induced errors in the measurement model, the system can be deployed along a deformed beam to enable synchronized dynamic measurements at multiple points. Comparative field tests demonstrate that the displacement measurements obtained from this system are consistent with those from traditional methods, such as manual leveling and automated connecting pipe systems, while providing advantages in terms of dynamic monitoring and the breadth of measurement parameters. Benefiting from real-time multipoint measurement, the system captures detailed spatial deformation curves. In addition, the observed vehicle-induced evolution of bridge deflection aligns well with the recorded vehicle speed and can be used to evaluate the modal parameters of beam bridges. The proposed method and system can provide new options and better data for bridge displacement monitoring to support the accuracy and timeliness of safety warnings. • A linear camera-chain measurement model derived from a pinhole imaging model is presented. • A follow-up visual measurement system is proposed that can be placed on deformable bridges. • Existing methods are compared with the proposed model for long-term successful verification. • Dynamic displacement time-space evolutions are discussed based on the all-span multipoint observations.

Computers in IndustryVol. 168
National University of Defense Technology (CN), Northwestern Polytechnical University (CN), Shenzhen University (CN), Shenzhen Technology University (CN)
Openalex Percentile: Top 28%
Structural Health Monitoring Techniques
0.95
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