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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/10121

Title: Adhesion estimation at the wheel–rail interface using advanced model-based filtering
Authors: Ward, Christopher P.
Goodall, Roger M.
Dixon, Roger
Charles, Guy
Keywords: Condition monitoring
Wheel–rail contact
Low adhesion
Advanced filtering
Real-time estimation
Fault diagnosis/detection
Issue Date: 2012
Publisher: © Taylor and Francis
Citation: WARD, C.P. ... et al, 2012. Adhesion estimation at the wheel–rail interface using advanced model-based filtering. Vehicle System Dynamics: international journal of vehicle mechanics and mobility, 50 (12), pp.1797-1816.
Abstract: The railway industry in the UK is currently expanding the use of condition monitoring of railway vehicles. These systems can be used to improve maintenance procedures or could potentially be used to monitor current vehicle running conditions without the use of cost prohibitive sensors. This paper looks at a novel method for the online detection of areas of low adhesion in the wheel/rail contact that cause significant disruption to the running of a network, particularly in the autumn season. The proposed method uses a Kalman–Bucy filter to estimate the creep forces in the wheel–rail contact area; post-processing is then applied to provide information indicative of the actual adhesion level. The algorithm uses data that, in practice, would be available from a set of modest cost inertial sensors mounted on the vehicle bogie and wheel-sets. The efficacy of the approach is demonstrated using simulation data from a nonlinear dynamic model of the vehicle and its track interface.
Description: This is an electronic version of an article published in Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility: http://www.tandfonline.com/doi/abs/10.1080/00423114.2012.707782
Version: Accepted for publication
DOI: 10.1080/00423114.2012.707782
URI: https://dspace.lboro.ac.uk/2134/10121
Publisher Link: http://dx.doi.org/10.1080/00423114.2012.707782
ISSN: 0042-3114
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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