VR FleetCare to introduce train automated detection device

Train ScannerThe Finnish rolling stock maintenance company VR FleetCare will deploy in June the Train Scanner, a device designed to automatically inspect the external condition of trains.

The device has been tested for one year and will inspect the Flirt commuter trains operating Helsinki’s rail network. The objective is to be able to reliably identify any malfunctions and stains on the exterior of trains.

The device has been developed in cooperation with VR FleetCare and Vire Labs, a Finnish company providing IoT solutions based on machine intelligence.

The Train Scanner is based on machine vision, shape recognition and artificial intelligence. 6.5-metre-high poles with scanners are installed on both sides of the track and used to scan the train that drives by.

The sides and roof of the train are scanned with a line camera with extremely high imaging speed and analysis accuracy, with a resolution of approximately a few millimetres. The data from the scanner is instantly processed by means of edge computing that analyses the data and reports any deviations. The information is instant available for the train maintenance operator and is also stored in a cloud service for further analysis.

“The shutter speed and resolution of the camera could be compared to photo-finish cameras used in sports competitions, for instance. We taught the device how a train should look like so that it can automatically detect any deviations. Artificial intelligence becomes increasingly more accurate based on the feedback the device receives from humans. The final objective is to be able to detect any rolling stock malfunctions in a reliable manner,” said Samuli Suuriniemi, Project Manager at VR FleetCare who oversaw the development work of Train Scanner.

Up until now, Train Scanner has been only tested with passenger trains but due to its scalability, the device can be used to inspect any rolling stock. In border control, for instance, the device could be used at border stations to automatically detect whether the size of a wagon adheres to the local instructions or used to verify the safety of wagons.


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