• ISSN: 1674-7461
  • CN: 11-5823/TU
  • Hosted by:China Society and Technology Association
  • Organizer:China Graphics Society
  • Guidance:China Academy of Building Research
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
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

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

  • 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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