Real-Time Monitoring of Displacement of Machine Vision Bridge Based on YOLOV5-MLR Study

Dong Ran, Dong Ran, Jianxu Long, Jianxu Long, Zhuan Wang, Zhuan Wang, Xiaoyong Zhang, Xiaoyong Zhang, Qian Guo, Qian Guo

2024

Abstract

Currently, the bridge maintenance tasks are arduous, and the health condition of bridges is of the utmost importance to ensure traffic safety. In order to achieve real-time monitoring of bridges and reduce monitoring costs, it is necessary to seek practical and effective solutions. Research has found that due to the influence of environmental and other factors, the precision and accuracy of traditional machine vision monitoring methods are insufficient. Therefore, this paper proposes a method called the YOLOV5-MLR improved algorithm. This algorithm adopts more complex texture targets and can better distinguish the surrounding environment during the monitoring process, thus improving the accuracy. In addition, during the calculation process, the algorithm refines the precision unit to the pixel level and can achieve a precision level at the sub-millimeter level. After a series of experimental verifications, the results show that the YOLOV5-MLR improved algorithm has high robustness, and the monitoring error is controlled at the millimeter level, meeting the specification requirements for bridge monitoring. This new algorithm provides important technical support for bridge health monitoring and is expected to play a key role in the field of bridge monitoring.

Paper Citation

in Harvard Style

Ran D., Long J., Wang Z., Zhang X. and Guo Q. (2024). Real-Time Monitoring of Displacement of Machine Vision Bridge Based on YOLOV5-MLR Study. In Proceedings of the 7th International Conference on Environmental Science and Civil Engineering - Volume 1: ICESCE; ISBN 978-989-758-764-1, SciTePress, pages 220-227. DOI: 10.5220/0013628000004671

in Bibtex Style

@conference{icesce24,
author={Dong Ran and Jianxu Long and Zhuan Wang and Xiaoyong Zhang and Qian Guo},
title={Real-Time Monitoring of Displacement of Machine Vision Bridge Based on YOLOV5-MLR Study},
booktitle={Proceedings of the 7th International Conference on Environmental Science and Civil Engineering - Volume 1: ICESCE},
year={2024},
pages={220-227},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013628000004671},
isbn={978-989-758-764-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Environmental Science and Civil Engineering - Volume 1: ICESCE
TI - Real-Time Monitoring of Displacement of Machine Vision Bridge Based on YOLOV5-MLR Study
SN - 978-989-758-764-1
AU - Ran D.
AU - Long J.
AU - Wang Z.
AU - Zhang X.
AU - Guo Q.
PY - 2024
SP - 220
EP - 227
DO - 10.5220/0013628000004671
PB - SciTePress