Damage assessment and online monitoring strategy for aging wind turbine foundations based on stiffness degradation

Abstract

Aging onshore wind turbines are prone to foundation damage, making robust structural health monitoring crucial. This paper presents a two-stage methodology for the online assessment and monitoring of such damage using operational data. The first stage, Model Validation, establishes a damage analysis model by calibrating force–displacement (F-D) curves with observed damage. Its physical accuracy is validated using turbine startup data, where hub rotational speed (ω) serves as a load proxy, confirming that the model’s nonlinear response aligns with field measurements. The second stage, Strategy Development, leverages this validated model to develop a robust, widely applicable monitoring strategy. This strategy uses tower vertical strain (ε _v ) as a direct, accurate proxy for the overturning moment, relevant across all operational regimes. From this strain data, a stiffness coefficient (K) is derived as a precise, real-time indicator of foundation health. The methodology’s effectiveness was demonstrated on a 2 MW turbine, exhibiting high sensitivity to stiffness degradation. A key contribution of this framework is a guideline for sensor placement: The optimal zone is 1.0 to 1.5 tower diameters above the foundation, providing an ideal balance between sensitivity to foundation damage and resilience to local boundary effects.