Reliable and efficient monitoring of railway infrastructure is essential to ensure the safety, availability, and long-term sustainability of rail transportation systems. While numerous tools and methodologies have been developed to monitor assets such as bridges, tracks, sleepers, joints, switches, and vehicle fleets, increasing demands for cost-effective maintenance, higher traffic volumes, and resilience to ageing and climate-related effects continue to drive the need for more scalable and data-driven monitoring solutions.

This special session focuses on emerging technologies and methodologies for railway infrastructure monitoring, with emphasis on their practical application to predictive maintenance, early damage detection, performance assessment, and system-level optimization. The session aims to bridge the gap between methodological advances and real-world implementation, highlighting approaches that support asset management and operational decision-making in railway systems.

• Contributions are invited on system identification and vibration-based structural health monitoring (SHM) methods for infrastructure and vehicles, including both direct sensing approaches (e.g., permanently installed sensor networks) and indirect or on-vehicle monitoring strategies. Topics of interest also include advanced data acquisition and analysis techniques, machine learning and AI-based methods, and their integration into railway monitoring frameworks.
• Relevant themes include operational modal analysis (OMA), statistical and stochastic system identification for parameter, state, and load estimation using physics-based or data-driven models, fault and anomaly detection, uncertainty quantification, optimal experimental design, and sensor placement. Contributions addressing structural prognosis and data-driven updating of performance and reliability predictions are also welcome.
• Submissions presenting experimental studies, field applications, or long-term monitoring data—particularly those demonstrating practical impact on maintenance planning and infrastructure management—are strongly encouraged. Advances in inspection and monitoring technologies such as ground-penetrating radar (GPR), laser-based systems, FBG-based sensors, inertial measurement units (IMUs), wireless sensing networks, and drone-based inspections are also within the scope of this session.

Keywords: Railway Infrastructure, Structural Health Monitoring, System Identification, Operational Modal Analysis, Data Driven Methods

Track chairs

Charikleia Stoura, ETH Zürich, Politecnico di Milano

Xudong Jian, ETH Zürich

Eleni Chatzi, ETH Zürich

Paolo Chiariotti, Politecnico di Milano