A system to predict ‘rough riding’ has been fitted to 80 trains running in Network Rail’s Wessex Region, as part of a wider trial.
Siemens Mobility’s Train-Borne Condition Monitoring System (TBCM) is being evaluated on South Western Railway rolling stock over a period of six months.
Siemens’ TBCM identifies sections of track that need attention by analysing data collected from trains equipped with a GSM-R cab radio. The application can be downloaded, with no need for new hardware.
The company says that in addition to rough-ride detection and prediction, TBCM can be used to identify and monitor voids in the track, and to detect potential major anomalies. It also shows the effectiveness of repair at sites where rough rides have previously been reported.
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Güntürk Üstün - 07/05/2022 07:12
By using the relevant innovative technology to predict where a section of track may require attention, preventative maintenance can be planned during times of quiet network traffic. Rather than being delayed by reactive maintenance based on driver reports of a bumpy ride that could indicate issues, passengers will therefore have a more reliable service, as well as a more comfortable ride. Before the trial, Siemens Mobility commissioned the University of Huddersfield to work on the simulation of track/vehicle interactions using historic raw track data from Network Rail. With specialist equipment and expertise in this field, the University is now using computer models of vehicles to provide insights to Siemens Mobility to enable the development of the rough-ride algorithm. Although it is in the early stages of the trial, their system is already performing extremely well, having successfully predicted a number of rough rides according to Munich based Siemens Mobility GmbH. Dr. Güntürk Üstün
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