Research on the Effectiveness of Hybrid Balance Optimization Algorithm in Fault Diagnosis of Wind Turbines

Validity research in fault diagnosis plays an important role in wind turbines, but there is the problem of inaccurate fault location. The traditional bee swarm algorithm cannot solve the fault location problem in wind turbines, and the effect is not satisfactory. Therefore, this paper proposes the effectiveness research in the fault diagnosis of wind turbines based on the hybrid balance optimization algorithm, and analyzes the effectiveness research in the fault diagnosis of wind turbines. Firstly, the simulated natural selection theory is used to locate the influencing factors, and the indicators is divided according to the requirements of the validity research in fault diagnosis to reduce the interference factors in the validity research in fault diagnosis. Then, the simulated natural selection theory is used to form a validity research scheme in fault diagnosis of mixed balance optimization algorithm, and the effectiveness research results in fault diagnosis is comprehensively analyzed influencing factors in validity research in fault diagnosis.