The Influence of Surface Defect Characteristic Factors of Wind Turbine Blades on Defect Detection Difficulty Under Complex Working Conditions

Wind energy has become one of the research hotspots for a wide range of scholars for its clean, green and renewable advantages. Wind energy is applied through wind turbine generators, in which the wind turbine blade is an important component to establish a link between wind energy and wind power generation. With the continuous development of wind power generation technology, the installed capacity is also increasing, and its safety and reliability has become a key issue. If the wind turbine blade is damaged by the influence of climate conditions, work load and other factors, it will affect the power generation efficiency, or lead to the paralysis of the wind turbine, so it is important to monitor the health state of the blade and identify the defects. In this paper, the influence of surface defect characteristic factors on the difficulty of defect detection is simulated through finite element analysis method, combined with infrared thermal imaging technology and heat transfer theory. The simulation results show that the larger the defect area and the more compact the shape, the easier the defect is identified. The findings of this paper can play an important role in optimizing the inspection strategy of wind turbine blades, improving the inspection efficiency and accuracy, and helping to realize the health monitoring and maintenance of wind turbine blades to ensure the stability and safety of wind power generation.