Development and Validation of Innovative Weighing in Motion Systems

Abstract

The development of an efficient Weigh-In-Motion (WIM) system, with the aim of estimating the axle loads of railway vehicles in motion, is quite interesting from both an industrial and academic point of view. Such systems, with which the loading conditions of a wide population of running vehicles can be verified, are very important from a safety and maintenance perspective. The evaluation of the axle load conditions is fundamental especially for freight wagons, more likely to be subjected at risk of unbalanced loads that may be extremely dangerous both for the vehicle running safety and the infrastructure integrity. In this way, potentially dangerous overloads or defect of rolling surfaces could be easily identified: in case of measured overloads, the axle could be identified and monitored with non-destructive controls to prevent the propagation of potentially dangerous fatigue cracks. Also peaks on the measured contact forces could be caused by wheel flats or other kinds of damages of the rolling surfaces which could be early identified saving both vehicle and railway line from the dangerous consequence of a prolonged exposure to irregular loads. As a consequence the WIM system could be used both as Prognostic and Diagnostic tool thanks to its capability of early identifying a minor fault condition which could cause, if ignored, potentially catastrophic events. The development, the simulation and the validation of the innovative WIM algorithm aimed at estimating the axle loads of railway vehicles will be presented in this paper. The innovative algorithm have been preliminary validated using experimental data provided by Ansaldo STS and further trained on FEM simulation results. Obtained results are quite encouraging considering that experimental results have been optained with an experimental layout optimized for a different WIM algorithm previously developed by Ansaldo STS which, after the comparison, turned out to be inferior both in terms of performances and reliability.