Abstract:Research purposes: Due to the closure and complexity of high-speed rail tracks, there are many restrictive factors in the process of detection, especially in high-speed rail bridges. Meanwhile, most of the existing management and maintenance technologies still rely on manual detection which consumes a lot of manpower and material resources, and limited detection efficiency. In this paper, a dynamic displacement measurement system based on machine vision is proposed to identify the structural deformation of high-speed rail bridges under operating conditions through field experiments. Research conclusions: (1) The dynamic displacement measurement system based on the machine vision method can better recognize the displacement changes of the structure and identify structural dynamic responses in the operating state. (2) The technology based on machine vision has many advantages such as non-contact, low cost, multi-point measurement and little interference to train operations. It can realize the monitoring of the structure state during non-"skylight" time, and improve the efficiency of management and maintenance. (3) The research results can meet the requirements of periodic inspection and long-term monitoring and provide significant support for the development of high-speed rail bridge inspection technology and the construction of health monitoring systems for high-speed rail bridges.
雷冬, 杜文康, 朱国靖, 李润璞. 基于机器视觉方法的高铁桥梁监测技术研究*[J]. 铁道工程学报, 2023, 40(3): 45-49.
LEI Dong, DU Wenkang, ZHU Guojing, LI Runpu. Research on the Monitoring Technology of High-speed Railway Bridge Based on Machine Vision Method. Journal of Railway Engineering Society, 2023, 40(3): 45-49.
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