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This paper presents the development of a multiple model estimation approach for the identification of the adhesion limit to overcome the problem of the wheel slip/slide at the rail wheel-rail contact. The contact characteristics at the rail wheel-rail interface are both highly nonlinear and subject to changes due to exposure to external contaminations. The detection of adhesion and its changes is therefore scientifically challenging, but would provide a critical information in the control of trains to avoid undesirable wear of the wheels/track but also the safety compromise of rail operations. This study exploits the variations in the dynamic behaviour of the railway wheelset caused by the contact condition changes and applies a bank of Kalman filters designed at selected operation points for the adhesion estimation. A fuzzy logic system is then developed to identify the contact conditions by examining the residuals from the Kalman filters.
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Hussain et al. (2012) studied this question.
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