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An integrated method for railway fastener defect detection and geometric parameter measurement using 3D line laser
Xiaocui Yuan1,2,3, Wenyu Liu1, Yongli Ma1
1School of Electrical Engineering, Nanchang Institute of Technology, Nanchang, China.
Plos One
|May 22, 2026
Summary
This study introduces an automated system using a 3D laser sensor for railway fastener inspection, improving defect detection and geometric measurement accuracy for safer, more efficient track maintenance.
Area of Science:
- Railway engineering
- Computer vision
- Sensor technology
Background:
- Railway fasteners are critical for track stability and safety.
- Current geometric parameter measurement relies on inefficient and error-prone manual methods.
- Automated defect detection exists but lacks precise geometric measurement capabilities.
Purpose of the Study:
- To develop an integrated method for automatic railway fastener defect detection and geometric parameter measurement.
- To enhance the efficiency and accuracy of railway track maintenance inspections.
- To replace manual inspection with an intelligent, unified framework.
Main Methods:
- Utilized a 3D line laser sensor to acquire RGB depth images and point clouds.
- Employed YOLOv8 for visual defect detection and intact fastener localization.
- Applied PointNet++ for fastener component segmentation and geometric parameter calculation.
Main Results:
- YOLOv8 achieved high precision (97.7%) and recall (95.9%) for defect detection.
- Geometric measurements met railway engineering tolerances, with most errors below 0.5mm.
- The system operates at 4.32 km/h, suitable for on-site, hand-pushed inspection.
Conclusions:
- The proposed integrated method effectively automates defect detection and geometric measurement.
- This system significantly improves the intelligence and efficiency of railway track maintenance.
- It offers a viable replacement for traditional manual inspection methods.
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