2024, 16(4): 81-85. doi: 10.16670/j.cnki.cn11-5823/tu.2024.04.15
基于三维扫描技术的钢轨接头自动建模与病害识别研究
上海工程技术大学 城市轨道交通学院，上海 201620 |
Automatic Modeling and Defect Identification of Rail Joints Based on 3D Scanning Technology
School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, China |
引用本文:
熊承莉, 路宏遥, 胡倩倩. 基于三维扫描技术的钢轨接头自动建模与病害识别研究[J]. 土木建筑工程信息技术,
2024, 16(4): 81-85.
doi: 10.16670/j.cnki.cn11-5823/tu.2024.04.15
Citation:
Chengli Xiong, Hongyao Lu, Qianqian Hu. Automatic Modeling and Defect Identification of Rail Joints Based on 3D Scanning Technology[J]. Journal of Information Technologyin Civil Engineering and Architecture,
2024, 16(4): 81-85.
doi: 10.16670/j.cnki.cn11-5823/tu.2024.04.15
摘要:随着铁路事业的迅速发展，我国对钢轨检修和维护的需求日益增加。为了提高钢轨检修的效率和准确性，本文基于数字化钢轨模型的建立，运用三维扫描设备对钢轨接头进行扫描，获取图像点云数据，处理和拼接点云数据，并建立BIM模型，实现钢轨接头病害的自动识别。通过可视化呈现钢轨接头，能够有效识别主要病害类型及误差数据，对钢轨接头病害进行评估，真实反映钢轨接头、接头夹板及螺栓等部件的病害情况，为铁路钢轨养护和维修工程的信息化和科学化管理提供借鉴。
Abstract: With the rapid advancement of China's railway industry, the demand for rail overhaul and maintenance is becoming increasingly pressing. To enhance the efficiency and accuracy of rail maintenance, this study leverages the establishment of digital rail models and 3D scanning technology. The research involves scanning rail joints with 3D equipment to capture image point cloud data, processing and stitching this data, constructing BIM models, and automating the identification of rail joint defects. This approach facilitates the visual representation of rail joints, accurately identifies principal defect types and measurement errors, and assesses the conditions of rail joints, joint splints, and bolts. The results provide a detailed reflection of these components' conditions and offer a basis for advancing the informatization and scientific management of railway maintenance and repair projects.
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