ABSTRACT
ABSTRACT: In the proposed work the authors illustrate an innovative estimation algorithm for Weigh-in-motion (WIM) applications in order to estimating the axle or wheel loads, adaptable to different train compositions. 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 both track and vehicle. The novelty of the proposed solution is the general approach that allows to manage different typologies of measurement chains and input signals (both experimental data and simulated ones) and even the good robustness against numerical noise. The algorithm has been tested under different operating conditions by means of a wide simulation campaign: good results have been obtained. Developments will be based on the experimental data provided by Ansaldo STS and ECM SpA that collaborated for the research activity.
