A Machine Vision System for Automated Joint Bar Inspection From a Moving Rail Vehicle

Abstract

Broken joint bars have been identified as one of the major causes of main line derailments in the US. On October 2006, the US Federal Railroad Administration issued a federal regulation that mandates periodic inspections to detect cracks and other indications of potential failures in CWR joints [1]. The rule requires periodic on-foot inspection or an approved alternative procedure providing equivalent or higher level of safety. This paper describes a new machine vision-based system for joint bars inspection at speeds up to 70 mph. Four line-scan cameras mounted on a hi-railer or full size rail vehicle continuously capture high resolution images from both sides of each rail. An on-board computer system analyzes these images in real time to detect the joint bars. Each joint bar image is automatically saved and analyzed for visible fatigue cracks. The images can also be analyzed for missing bolts and other defects. When a potential defect is detected, the system provides audio warning, tags the image with GPS position, and displays the joint bar image with highlighted defects on the screen. The operator may confirm or reject defects. At the end of the survey, the operator can generate a survey report with the joint bar GPS location and types of all defects. This new system improves productivity and workers safety, inspecting joint bars from a moving vehicle instead of having to walk along highly transited tracks. It also allows the railroads to reduce the time between inspections, preventing defects to develop into hazards. Several tests have been performed on different rail roads showing system defect detection capabilities on both CWR and jointed track.