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Rollingstock Monitoring and Maintenance

We conduct research into advanced rolling stock monitoring and maintenance technologies aimed at extending asset life, improving operational safety, and reducing lifecycle costs.

Key areas of focus include digital twin-enabled predictive modelling, subsystem condition monitoring, and data-driven maintenance strategies.

Our research includes real-time monitoring of both mechanical subsystems—such as doors, wheelsets, and pantographs—and electrical components, including traction motors, transformers, and battery packs. These developments are supported by next-generation 5G/6G communication technologies, enabling reliable, high-speed transmission of condition data from individual trains to central monitoring platforms.

In predictive maintenance, we are developing methods for wheel degradation forecasting, vision-based AI defect detection, and advanced analytics to support rapid decision-making and targeted interventions.

Our research into digital twinning includes simulation and analysis of pantograph aerodynamics, electromagnetic compatibility, and noise and vibration behaviour, supporting more efficient, accurate modelling of in-service performance. 

Meet the team

  • Dr Simon Bale - Senior Lecturer, School of Physics, Engineering and Technology
  • Professor David Grace - Professor (Research), Head of Communication Technologies Research Group, Co-Director of York - Zhejiang Lab for Cognitive Radio and Green Communications, Guest Professor Zhejiang University
  • Peter Ellison - Lecturer in Clinical Engineering, School of Physics, Engineering and Technology
  • Dr Mohammad Nasr Esfahani - Senior Lecturer, Director of Teaching and Learning (Engineering), School of Physics, Engineering and Technology
  • Dr John Oyekan - Senior Lecturer, Department of Computer Science
  • Suresh Perinpanayagam - Professor of Engineering, School of Physics, Engineering and Technology
  • Dr Jiannan Yang - Lecturer in Digital Engineering for Future Technologies, School of Physics, Engineering and Technology. 
  • Dr Xing Zhao - Lecturer in Electrical Engineering, School of Physics, Engineering and Technology

 

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