The Resilience of Vision-Based Technology for Railway Track bed Monitoring

Abstract

Innovative non-contact sensing and monitoring systems based on Vision-Based (VB) technology are becoming a viable method to remotely capture railway track vibrations and quality. This paper describes the use of VB system for the measurement of track vertical displacements and the estimation of track stiffness. The dynamic response of the track under a moving vehicle load was investigated through experimental and numerical modelling using a series of large-scale trails and finite element (FE) simulations. The accuracy of the VB system was examined with a conventional sensor used to measure the rail deflection. The viability of VB system in detecting voids between rail and sleeper due to faults in fastening were discussed. Results obtained from the VB monitoring was then used to calibrate FE models used to estimate the subsoil stiffness. The paper concludes with a discussion of how this methodology can be utilised in the railway industry for assessing the track performance with less complicated and more cost-effective hardware compared to conventional monitoring systems.