Abstract Summary
Operating wind turbines are complex systems due to fluctuating aerodynamic loads induced by turbulent wind fields, rotor rotation and the tower-rotor coupling dynamics. Difficulties have been claimed in structural identification of operating wind turbines using traditional operational modal techniques due to harmonics in responses caused by rotor rotation and time-invariant nature of such systems. Structural identification of full-size wind turbines through field measurement is even more difficult due to uncertainties of ambient excitations. In this study, structural identification is conducted to a carefully designed scale-down wind turbine model. Rotor rotation is realised via a motor and the influence of different wind fields is studied by wind tunnel tests. Dynamic responses of the blades and tower are measured through Digital Image Correlation (DIC), and the measured responses are processed by different system identification techniques including traditional Stochastic Subspace Identification (SSI) and specifically developed identification method based on Bayesian inference. It is found the later method can successfully identify the key modal parameters of the wind turbine model with sufficient accuracy, and these parameters are comparable to those of the prototype wind turbine.
