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 model-based approach that uses a Kalman-Bucy filter to estimate creep forces, with subsequent post processing for interpretation into 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.
|Number of pages||12|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit|
|Early online date||18 Sep 2013|
|Publication status||Published - 1 Nov 2013|