Railway Track Inspection on-the-Go
Defects in rail tracks can result in revenue loss and even death in some cases. The most common type of inspection is manual, in which a gang man inspects five to six kilometers per day. Manual inspections cover a small area per day, resulting in a high likelihood of defects going undetected.
In this paper, we present a case study of how the hybrid solution for railway track inspection has proven effective, reducing the need for continuous processing of huge 2D laser data sets.
For surface defect detection, camera pictures are first captured and then the 3D profile or point cloud of the laser scanner is analyzed to determine the exact nature of the defect.
The application's analytics can predict errors before they become obvious, helping to reduce the number of collisions between humans and objects in the environment.