Overview
Digital transformation of tunnel maintenance information
Previous management relied on diesel or water-spraying vehicles
Low-speed (10–15 km/hr), night-only operation
New vehicle achieves 99% efficiency at 40–70 km/hr
Enables daytime operation with reduced passenger exposure to fine dust
Core Competencies
Purpose
Analyzing 3D point cloud data manually is time-consuming, with low reliability and efficiency, making real-time analysis of tunnel shapes impossible. LiDAR-based automated 3D shape analysis aims to automatically analyze LiDAR data to evaluate the status of tunnel shapes in real time.
• Collecting on-site image with LiDAR
• Generating 3D point cloud data with LiDAR
• Measuring the full tunnel cross-section
• Classifying objects automatically
• Defining 3D geometric information
• Constructing 3D point cloud data
• Providing digital twin connectivity solution
• Providing time series analytics technology
Expected Benefits
Labor Cost Reduction – Automated measurement
Systematic management of tunnel shape information
Real time geometry assessment
Linkage: Digital twin technology
TRL 7
Contact
Korea Railroad Research Institute (KRRI)
Global Business Department
Dr. Jeongjun Park
E-mail: jjpark@krri.re.kr