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Aided by its intelligent laser sensors, the rail-road vehicle carries out a diagnosis of the tramway infrastructures within the Grenoble conurbation. An innovative technology made for the roads, which would considerably reduce the inspection time of the 53 km of the network. #IOLS
Previously, the diagnosis of the condition of the 53 km of tramway network in the Grenoble conurbation took nearly a month for the dedicated agents. With company-tested technology Viapix System, the tests are carried out in one day. The French leader in this kind of artificial intelligence performs an assessment of the condition of the rails in record time.
The system is still in the testing phases. The goal is to be able to develop a viable process for auscultating infrastructures.“These data are integrated into automatic processing software based on AI which will make it possible to inventory the state of the network, the pathologies detected on the rails or the signaling”describes a technician.
This is one of the first European experiments with this technology. “The precision will be of the order of a millimeter on the longitudinal and 0.1 millimeters for the depth, i.e. the possibility of locating the slightest crack on a rail”explains Clément Gutierrez, technical director at Viapix System. This system, once implemented, would provide the assurance of better anticipating breakdowns, as explained by Christine Rochex, technical director at the Transport Department of the Grenoble Agglomeration: “The goal is for citizens to have trams on the tracks as often as possible. By detecting problems upstream, we manage to control our maintenance costs.”
This experiment is the result of a partnership between Viapix System and the Transport Department of the Grenoble Agglomeration. For the first, the agreement gives an opportunity to test the effectiveness of their vehicle equipped with artificial intelligence in real conditions, for a release scheduled for 2023. With regard to the second, the objective is thus to ensure better service to users by anticipating potential damage.
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