Adhesion estimation at the wheel–rail interface using advanced model-based filtering
2012-07-25T15:23:22Z (GMT) by
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.