In the present work the authors propose an innovative estimation algorithm for Weigh-in-motion (WIM) applications with the aim of estimating the axle or wheel loads of a generic train composition, starting from indirect track measurements. The WIM algorithm elaborates the set of experimental physical quantities chosen as track inputs, making use of estimation procedures based on least square minimization techniques. To perform an accurate estimation, the algorithm uses a flexible multibody model of the track and the vehicle. The novelty of the proposed solution is the general approach that allows to manage different kinds of measurement station and signal inputs (both experimental data and simulated ones) and the good robustness against numerical noise. The algorithm has been tested under any operating conditions through a wide simulation campaign, obtaining good results. Future developments will be based on the experimental data provided by Ansaldo STS and ECM SpA that supported the research activity.

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