While rail freight transportation is gradually becoming a crucial asset in the context of decarbonization of the transport sector, new standards and requirements in this field aim at improving the safety and reliability of freight vehicles and the infrastructure. From this perspective, Condition Monitoring and Condition Based Maintenance are becoming essential tools to improve systems reliability through the use of in-service instrumented vehicles. On the contrary of high-speed applications, freight trains are actually not provided with any monitoring systems able to carry out this kind of analyses. In this context, an innovative hybrid monitoring system composed by wireless sensor nodes and a gateway was developed to be suitably mounted on a freight wagon. Sensor nodes, power supplied by solar energy, are able to carry out synthetic indices from vibration measurements, while the gateway acquires correlated GPS and odometry information. In order to take advantage of the acquired data, a software based on a geo-localization algorithm created for high-speed applications was developed in order to correlate vibration data to the railway line mileage. A field campaign allowed to test the system on a real freight wagon and to acquire many experimental data. Using the collected experimental data, in the paper is shown how the developed software can be used to perform diagnostic activities of the infrastructure. Moreover, it is demonstrated that relying on the only GPS information is sufficient to get enough accurate georeferenced data for freight trains applications. This paves the way to the future development of a completely wireless system able to perform condition monitoring of both the vehicle and the infrastructure minimizing the impact on the vehicle.


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    Titel :

    Wireless sensor nodes for freight trains condition monitoring based on geo-localized vibration measurements


    Beteiligte:


    Erscheinungsdatum :

    01.02.2023


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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