This special session deals with structural health monitoring (SHM) of wind turbines and farms. SHM can be employed for early-stage damage detection and to explore uncertainties in the design, provide early alerts for degradation, damage, and detect abnormal operations. It can also offer valuable insights for future design improvements and operational optimisation. This session focuses on the integration of sensing techniques for digital twinning, condition-based maintenance, population and fleet based monitoring and the assessment of life-cycle and remaining useful lifetime for wind energy structures and farms. SHM applications include, but are not limited to, measuring environmental inflow conditions, monitoring wind turbine performance, evaluating structural load impacts (both extreme and fatigue cycles), analysing system dynamics, assessing modal and physical properties.

Papers dealing with the following subjects are especially welcomed:

• Real-time schemes for efficent monitoring and diagnostics.
• Data-driven and physics-informed methods for virtual sensing and digital twinning.
• Physics-constrained machine learning applications.
• Experimental investigation and verification of analysis schemes.
• Population and fleet based monitoring of wind farms.
• Load and latent force estimation via system identification tools.

Keywords: Structural Health Monitoring, Wind Energy Structures, Wind Farms

Track chairs

Eleni Chatzi, ETH Zürich

Nikolaos Dervilis, University of Sheffield

Ivan Au, Nanyang Technological University Singapore