Urban rail transport is under constant pressure. Tight curve radii, high frequencies, and increasing environmental demands lead to familiar challenges: squealing on curves, increased wheel-rail wear, and the use of lubricants with negative environmental impacts.
Conventional rail head lubrication is largely static, using fixed quantities at fixed locations, regardless of weather or actual need. This often creates a trade-off between noise, wear and environmental impact.
This is where the intelligent rail head lubrication research project comes in. Requirements are determined based on data, using:
- acoustic sensors directly on the vehicle
- continuous noise mapping along the route
- weather and operating data
- AI-supported evaluation
This means that lubrication is triggered depending on the situation and proactively, based on real operating data. This is the starting point for our research.
More background on the intelligent rail head lubrication research project, including objectives, approach and system architecture, can be found here:
– Project description: https://www.aramis.admin.ch/Default?DocumentID=73688&Load=true
– Project presentation (overview and setup, only in German): aramis.admin.ch/Default?DocumentID=73691&Load=true
