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Computer vision-based real-time monitoring for swivel construction of bridges: from laboratory study to a pilot application

Shilong Zhang (Harbin Institute of Technology, Harbin, China)
Changyong Liu (Harbin Institute of Technology, Harbin, China)
Kailun Feng (Harbin Institute of Technology, Harbin, China)
Chunlai Xia (Harbin Institute of Technology, Harbin, China)
Yuyin Wang (Harbin Institute of Technology, Harbin, China)
Qinghe Wang (Shenyang Jianzhu University, Shenyang, China) (Harbin Institute of Technology, Harbin, China)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 16 April 2024

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Abstract

Purpose

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

Design/methodology/approach

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

Findings

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

Originality/value

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

Keywords

Acknowledgements

This project was funded by the National Natural Science Foundation of China (grant no. 52108279), the China Postdoctoral Science Foundation (grant no. 2020M670918), the Research on The Improvement of High-Level Service Ability of Whole-Process Engineering Consulting (grant no. R20210505, China Ministry of Housing and Urban-Rural Development), Liaoning Research Project, China (grant no. lnjc202007), and by Shenyang Science and Technology Project, China (grant no. RC200143).

Citation

Zhang, S., Liu, C., Feng, K., Xia, C., Wang, Y. and Wang, Q. (2024), "Computer vision-based real-time monitoring for swivel construction of bridges: from laboratory study to a pilot application", Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-10-2022-0992

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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