The need for predictive maintenance of wind turbines has increased. Prognostics and Health Management research is working on estimating the Remaining Useful Life with greater accuracy and to determine future operating conditions, taking into account system constraints on safety and reliability when power generation capacity is also an issue. Torsional phenomena contribute to wind turbine life degradation, and the rate of degradation depends on wind profiles. To meet health management requirements, deterioration-aware control plays a role in adjusting control responses to mitigate the resulting stress depending on known wind parameters that characterize different wind speed conditions. Therefore, a degradation analysis is proposed to analyze the degradation results for different Ornstein-Uhlenbeck parameters that express the wind speed and can be estimated with a standard Kalman Filter.