Intelligent optimization for bending moment in uniaxial fatigue loading test of wind turbine blades

Abstract

Wind turbine mainly relies on blades to capture wind energy and complete energy conversion. Wind turbine blade is one of the key components of wind turbine. In the full scale load test of wind turbine blade, the moment matching is the key part of the test and the premise of wind turbine blade certification. In order to solve the matching problem of the bending moment and the arrangement of counterweight in the fatigue loading test, an improved intelligent optimization algorithm was proposed to achieve the purpose of moment matching. The relationship between the excitation frequency of the rotating mass and the natural frequency of the blade was determined through the identification of the modal test parameters, and the calculation model of the section bending moment was constructed. Based on the optimization algorithm, the joint optimization of moment distribution and amplitude control was carried out with the mean square error as the fitness function. The correctness and feasibility of the balance weight optimization scheme for moment matching in uniaxial fatigue test were verified through the blade test.