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Real time detection of low adhesion in the wheel/rail contact

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journal contribution
posted on 24.09.2018, 10:58 by Peter HubbardPeter Hubbard, Christopher WardChristopher Ward, Roger Dixon, Roger Goodall
Condition monitoring of railway vehicles has been highlighted by the railway industry as a key enabling technology for future system development. The primary uses for this could be the improvement of maintenance procedures and/or the identification of high risk vehicle running conditions. Advanced processing of signals means these tasks could be accomplished without the use of cost prohibitive sensors. This paper presents a system for the on-board detection of low adhesion conditions during the normal operation of a railway vehicle. Two different processing methods are introduced. The first method is a modelbased approach that uses a Kalman-Bucy filter to estimate creep forces, with subsequent post processing for interpretation in to adhesion levels. The second non model-based method targets the assessment of relationships between vehicle dynamic responses to observe any behavioural differences as a result of an adhesion level change. Both methods are evaluated in specific case studies using a British Rail (BR) Mark 3 coach, inclusive of a BR BT-10 bogie, and a generic modern passenger vehicle based on a contemporary bogie design. These vehicles were chosen as typical application opportunities within the UK. The results are validated with data generated by the multi-body simulation software VAMPIRE® for realistic data inputs, representing a key scientific achievement


This work was supported in part by RSSB under the project number T959.



  • Mechanical, Electrical and Manufacturing Engineering

Published in

IMechE Part F: Journal of Rail and Rapid Transit




623 - 634 (11)


HUBBARD, P.D. ... et al., 2013. Real time detection of low adhesion in the wheel/rail contact. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 227(6), pp. 623-634.


© IMechE. Published by Sage


AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date



This paper was accepted for publication in the journal Dalton Transactions and the definitive published version is available at https://doi.org/10.1177/0954409713503634