Predictive wheel–rail management in London Underground: Validation and verification

Abstract

London Underground is facing the challenge of increasing timetables against spending cuts across renewals and maintenance in all assets. In order to meet this challenge, it is reviewing all maintenance practices to make sure that they are appropriate for the current asset conditions. Management of the wheel–rail interface is critical to maximising the life of wheels and rails through preventative maintenance regimes that ensure all activities offer value for money and safe operation. Detailed monitoring of the asset condition using novel non-destructive techniques has allowed the identification of the problems which currently occur at the wheel–rail interface on the London Underground network. These problems are discussed in this paper along with some of the solutions proposed to manage them. Site observations from a range of rail rolling contact fatigue monitoring sites have also been compared to the outputs from vehicle dynamic simulations. These outputs were post-processed using a circle plotting technique, which illustrates the location, direction and severity of the forces, and the Whole Life Rail Model to predict the susceptibility to rail damage for two rail steel grades. The outputs from these comparisons have helped to illustrate the wheel–rail contact conditions and forces which are driving the observed damage and potential future enhancements to improve the accuracy of the models for predicting the observed rolling contact fatigue damage.