Automatic Modeling and Defect Identification of Rail Joints Based on 3D Scanning Technology

Chengli Xiong; Hongyao Lu; Qianqian Hu

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. Journal of Information Technologyin Civil Engineering and Architecture, 2024, 16(4): 81-85. doi: 10.16670/j.cnki.cn11-5823/tu.2024.04.15

2024, 16(4): 81-85. doi: 10.16670/j.cnki.cn11-5823/tu.2024.04.15

Automatic Modeling and Defect Identification of Rail Joints Based on 3D Scanning Technology

Chengli Xiong , Hongyao Lu ^,, Qianqian Hu

School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, China

Corresponding author: 路宏遥,

Web Publishing Date: 2024-08-20

Fund Project: 上海市大学生创新训练项目“基于数字孪生的轨道板缺陷检测系统” cs2310003上海工程技术大学产教融合课程建设项目“铁道工程BIM课程设计” k202310002

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.

Key words: Rail Joints, 3D Scanning, Point Cloud Data, BIM, Maintenance

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