Automated visual inspection for underbody equipment of railway vehicles

(evaluation of diagnostic performance of images taken over a long term of real vehicle and a simulated vehicle with anomalies)

Abstract

The authors developed an imaging system and a diagnostic algorithm for automated visual inspection of underfloor equipment on passenger rail vehicles. The developed imaging system was installed for testing in a railway yard and recorded many images of rolling stock passing in front of the system for about a year. The system also recorded images of a test train simulating various visual anomalies on the underfloor equipment. The developed diagnostic algorithm was applied to the recorded images to evaluate its diagnostic performance. The results revealed the types of anomalies that can be detected by the proposed algorithm, and the influence of sunlight and rainfall on the diagnostic performance.