A new Model Based Estimation Algorithm for Train Axle Counting and Detection

This paper presents an innovative train detection algorithm, able to perform the train localization and, at the same time, to estimate its speed, the crossing times on a fixed point of the track and the axle number. The algorithm can manage different types of input, measured on the track: more particularly, all the inputs are processed through cross-correlation operations to extract the required information. A suitable and accurate multibody model of railway vehicle and flexible track has been also developed by the authors to test the algorithm when experimental data are not available.