With global warming, increasing environmental pollution and the increasing consumption of fossil energy, wind energy, as a clean and renewable energy source, has gradually been emphasized. At present, the wind power market is growing rapidly, and the wind turbine blade defect detection has attracted the common attention of engineers and researchers, which directly affects the safe operation and economic benefits of wind farms. This paper first establishes a heat transfer mathematical model based on the theory of heat transfer and finite element thermal analysis, and then simulates the influence of longitudinal defect characteristic factors on the degree of difficulty of defect detection using ANSYS. The simulation results show that the shallower the defect burial depth and the deeper the defect depth, the easier the defect is recognized. The findings of this paper can provide an important reference basis for the accurate detection of wind turbine blade defects, and at the same time provide a strong theoretical support for guaranteeing the safe operation of wind farms.