Short title: WetProRail

Long title: Weather-based Forecasting Model to Map the Relationship between Weather and Wheel/Rail Contact

Assignment to our (IMW) research priorities:

  • Data Analysis
  • Predictive Modeling & Machine Learning
  • Maintenance


Siemens Mobility (Link:, opens an external URL in a new window)

Duration: 2022 - 2023


WetProRail addresses the influence of weather conditions on slip and traction parameters in rail vehicle maintenance. The coefficient of friction, which is influenced by factors such as rolling speed, normal load and surface roughness, has a significant effect on slip and traction. Lubrication condition and contact temperature also play a significant role. Integrating weather conditions into the analysis presents challenges, including linking and synchronising driving data with weather data, and understanding the correlation between weather parameters and wheel-rail contact. Predicting slip and traction parameters based on weather conditions becomes critical to implementing real-time analysis, enabling predictive maintenance strategies and reducing the risk of damage. By addressing these challenges, optimal maintenance strategies can be developed, failures can be reduced, and maintenance actions can be performed at the appropriate time to ensure safe and efficient rail operations.


  • Linking and synchronising a train's sensor data with historical weather data
  • Calculation of correlation for different contact and weather parameters
  • Developing a machine learning based model to predict the state of the contact conditions between the wheel and the rail of a railway system based on current weather conditions


Siemens Mobility (Link:, opens an external URL in a new window)

Project Management:

Dipl.-Ing. Theresa Madreiter

Telephone: +43 1 58801 33051