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DMrail - digital maintenance for a sustainable railway infrastructure

Reference number
Coordinator RISE Research Institutes of Sweden AB - RISE RESEARCH INSTITUTES OF SWEDEN AB, VÄSTERÅS
Funding from Vinnova SEK 4 411 951
Project duration June 2019 - August 2022
Status Completed
Venture The strategic innovation program InfraSweden
Call Solutions for sustainable transport infrastructure

Purpose and goal

DMrail aimed at improving existing state-of-practice maintenance systems in order to increase the operational uptime of rail infrastructure. Innovative methods for continuous health monitoring, data driven decision making, and efficient allocation of maintenance resources wanted to be utilized to this aim. DMrail aimed at addressing the digitalization dimension of the InfraSweden2030 and brings us one step closer to a connected transportation vision.

Expected effects and result

The innovation potential has been built around creating simple innovative measuring methods, and trouble-free installation and rational (dynamic) data transfer that is sufficient for an automated remote condition diagnostics and analysis that trigger maintenance activities as needed. The validation of project results was key driver. Real Bombardier data sets have been used for assessing the validity of the solutions including Cloud and Edge ML anomaly detections. The Trafikverket’s Ofelia database allowed us to analyze actual faults and compare them with our algorithms.

Planned approach and implementation

The project was performed though the collaboration between the actors in the project consortium - toward a highly innovative technological solutions for train communication infrastructure and railway signaling systems (with enhanced survivability support). The DMrail dynamic data-driven predictive maintenance methods has been defined and validated by the infrastructure owners’ and based on their needs - primarily aimed at reducing the fault outcome on the key functions of switches and track circuits.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 14 October 2022

Reference number 2019-01112

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