Lidar-IMU-GPS Based System for Over Head Contact Line Geometry Assessment in Railways

This work explores the feasibility of a LiDAR-IMU-GPS-based multi-sensor system for assessing the geometrical configuration of Overhead Electrical Equipment (OHE) in Indian Railways. With over $100,000 \mathrm{~km}$ of track, periodic OHE inspections remain largely manual, impacting operational efficiency. Key parameters such as contact wire height and stagger directly affect pantograph performance and train operations. To automate these measurements, a field experiment was conducted using a roof-mounted sensor system on a railway inspection car over a 9 km stretch, capturing OHE point cloud data. The proposed method employs region-of-interest segmentation, mean height-based segmentation, and projected 2D clustering to extract OHE profiles. Contact wire height measurements were validated against manual measurement data, achieving an accuracy of over 99.34%. The results demonstrate that this approach is a viable alternative to manual OHE assessments, enhancing both efficiency and reliability in railway electrification.