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

火车 全球定位系统 背景(考古学) 默认网关 状态监测 无线 计算机科学 可靠性(半导体) 无线传感器网络 辅助全球定位系统 实时计算 软件 铁路货物运输 汽车工程 工程类 电信 计算机网络 功率(物理) 电气工程 古生物学 物理 地图学 量子力学 生物 程序设计语言 地理
作者
Federico Zanelli,Edoardo Sabbioni,Marco Carnevale,Marco Mauri,Davide Tarsitano,Francesco Castelli Dezza,Nicola Debattisti
出处
期刊:Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit [SAGE]
卷期号:237 (2): 193-204 被引量:15
标识
DOI:10.1177/09544097221100676
摘要

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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