Load parameter identification of wind turbine rotor involving probability and interval variables

Knowledge of the load parameters of wind turbine rotor is the key problem to eliminate the misalignment of wind turbine. In this paper, an inverse method for identifying the load parameters with imprecise information is investigated by using the probability and interval variables. The interval variables are dealt with interval analysis, only the bounds of the structure response are needed avoiding time-consuming inner loop for structure response prediction. The probability variables are dealt with a proposed iteration method combined micro genetic algorithm with the search interval advance and retreat method. Firstly, at the midpoint of the interval variables, the mean of the load parameters is identified based on the proposed iteration method; secondly, the first-order Taylor expansion is employed to gain the boundary of rotor dynamic response from predicting structure response strip derived from the existence of interval variables; thirdly, the interval of the load parameters is identified via the boundary of rotor dynamic response based on the proposed iteration method. Eventually, the accuracy and efficiency of the proposed inverse method are verified by one numerical example.