Fault detection of railway vehicle suspensions using multiple model approach

This paper describes the estimation algorithm of the fault detection of railway vehicles. This algorithm is formulated based on the interacting multiple-model (IMM) algorithm. IMM algorithm which choose probable model from number of models is applied to the fault detection. In IMM method, changes of the systems structure and the systems parameters are called mode. We provide several suspension failure modes and sensor failure modes for the fault detection. The mode probabilities and states of vehicle suspension are estimated based on Kalman filter (KF). This algorithm is evaluated in simulation examples. Simulation results show that the algorithm is effective for on-board fault detection of the railway vehicle suspension.