Increased patronage of railways in the UK in the past 20 years has put demands on rolling stock to operate at peak availability with reduced time available for maintenance. One possible tool to enable this is the use of real time fault detection and diagnosis on board railway vehicles to detect faulty components and provide information about the current running condition of the system. This paper discusses the development of one such technique for the estimation of creep forces of the wheel-rail contact. Real time knowledge of which could be used to predict wear of the wheel tread and rail head, predict the formation of rolling contact fatigue, and identify any areas of low adhesion present on the network. The paper covers development of a full vehicle nonlinear contact mechanics model, development of the Kalman-Bucy filter estimation technique and how the technique will be developed and validated in the future.
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