A Novel Wind Turbine Blade Life Extension Assessment Model Considering Stiffness Degradation

In order to determine the service life of wind turbine blades (WTB) and extend their service life, a life extension assessment model for WTB is proposed based on support vector regression (SVR) considering stiffness degradation. First, the advantages of stiffness performance indexes are selected to assess the life of in-service blades. The stiffness degradation rule is studied about turbine blade. Furthermore, the relationship between WTB life and stiffness is discussed to clarify the factors of the life extension model. Based on stiffness indicator, the support vector regression algorithm (SVR) is used to establish a life extension assessment model for WTB. Particle swarm optimization (PSO) is used to optimize the model parameters. The optimized model is trained and validated using WTB degradation stiffness data. Finally, the results show that the proposed model is effective in life extension assessment of WTB. The model with radial basis as the kernel function has a high goodness of fit.