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POT Bearings Monitoring in High-speed Railway Bridges

POT Bearings Monitoring in High-speed Railway Bridges

May 12, 2026 | Uncategorized

Challenge

POT bearings in viaducts are difficult to monitor continuously, leaving limited insight into their structural health and long-term degradation. Conventional inspection methods fail to capture real-time displacements, rotations, and environmental influences affecting performance. This restricts early detection of faults and weakens predictive maintenance and bridge management capabilities.

 The solution

Thanks to a comprehensive system for the monitoring of POT bearings in viaducts, this solution provides:

  • Integrated multi-sensor structural health monitoring system: combines Linear Variable Differential Transformers (LVDTs), inclinometers, triaxial accelerometers (30 units) and environmental sensors (temperature and weather stations) to continuously measure relative deck–pier displacements, pier rotations and dynamic response under train traffic and environmental actions. This enables detailed assessment of bearing (POT) performance, thermal effects and structural boundary conditions.
  • Real-time anomaly detection using advanced analytics and AI: applies Operational Modal Analysis (OMA) to extract modal parameters (frequencies, mode shapes, damping) and removes environmental influence through Linear Regression Models. Anomaly detection is performed using statistical control charts (e.g., Hotelling’s T²) and AI-based models that replicate POT bearing behaviour, allowing continuous inverse calibration and localisation of stiffness changes.
  • Predictive maintenance and intelligent bridge management: addresses the need to detect early degradation of sliding bearings (e.g., Polytetrafluoroethylene wear), correlates traffic and environmental effects and optimises preventive maintenance. The system delivers automated, real-time structural condition indicators and early warnings, improving safety, cost-efficiency, sustainability and supporting the development of smart railway bridge management methodologies.

Readiness for Industrialisation and Deployment

The system is currently in pilot phase and being tested in a real passenger high-speed railway environment.

  • It consists of a fully deployed prototype installed on an operational railway viaduct, where it is continuously monitoring structural behaviour under real passenger train traffic and environmental actions.
  • The solution integrates hardware (multi-sensor network) and software (OMA, AI-based bearing models, real-time anomaly detection), operating in an automated workflow.
  • It is already being tested in a specific market segment: high-speed passenger rail infrastructure.

 

Current stage (2025–2026):

  • Prototype demonstrated in operational environment (TRL 7).
  • Ongoing validation of dynamic indicators, anomaly detection algorithms and correlation with inspections and bearing performance.

 

Indicative timeline:

  • 2026: consolidation of results, extended monitoring period and validation across additional structures.
  • 2027+: scalable deployment to additional bridges within railway networks and preparation for broader integration into asset management systems.

The solution is therefore not yet fully commercialised for network-wide integration, but it is beyond laboratory validation and it is actively operating in a real railway market environment.

Maturity level

TRL 7 (System prototype demonstration in operational environment )

Expected benefits

  • Technical advantages: enables continuous, multi-parameter structural health monitoring combining static and dynamic measurements. Advanced analytics (OMA, AI-based bearing models, real-time anomaly detection) allow early identification of stiffness loss, abnormal boundary conditions and POT bearing degradation before visible damage occurs.
  • Operational benefits: supports predictive and condition-based maintenance instead of reactive interventions. Real-time alerts and automated indicators help prioritise inspections, reduce unplanned closures and improve service reliability in high-speed passenger lines.
  • Economic impact: optimises maintenance planning, extends bearing and structural service life and reduces unnecessary inspections or premature replacements, leading to significant lifecycle cost savings for infrastructure managers.
  • Environmental and sustainability benefits: by extending asset lifespan and reducing major corrective interventions, the system lowers material consumption, resource use and associated CO₂ emissions, contributing to more sustainable railway infrastructure management.
  • Strategic value: facilitates the transition toward intelligent, data-driven bridge management, positioning railway networks at the forefront of predictive maintenance and digital infrastructure innovation.

Who benefits

Infrastructure Managers

Railway operators

Suppliers

Final users

Conclusion

Thanks to a comprehensive system for the monitoring of POT bearings in viaducts, this solution can benefit as the main customer

  • The infrastructure managers, as they are responsible for bridge asset management, maintenance planning, safety assurance and lifecycle cost optimisation. The system directly supports their decision-making through real-time structural condition indicators and predictive maintenance tools.

Secondary beneficiaries are:

  • Railway operators: benefit indirectly through improved infrastructure reliability, reduced service disruptions and enhanced safety for passenger or freight operations.
  • Maintenance contractors and engineering suppliers: gain access to advanced diagnostic data that enables targeted interventions and optimised maintenance strategies.
  • Final users (passengers and freight customers): benefit indirectly from increased safety, service continuity and reduced risk of infrastructure-related delays.

Learn more about the project

FP3-IAM4RAIL

This solution has been developed within the Europe’s Rail (EU-Rail) Flagship Project FP3-IAM4RAIL. The project FP3-IAM4RAIL focuses on seven different integrated demonstrators for rail assets which are key for research and innovation in the rail sector.

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