To address the high computational cost and significant errors in the fatigue analysis of floating offshore wind turbines, this study proposes a computational method based on statistical linearization and an improved frequency band method for analyzing the fatigue performance of the tower bottom. The statistical linearization algorithm is introduced to process the nonlinear coupled dynamic model of floating offshore wind turbines, enhancing the computational efficiency of hot spot stress. Meanwhile, the traditional frequency band method is refined by modifying the probability density function of stress amplitude to accurately capture the multi-peak characteristics of the stress response spectrum of floating offshore wind turbines, thereby improving fatigue analysis accuracy. Taking a Spar-type floating offshore wind turbine as an example, the proposed method is applied to analyze the tower bottom fatigue performance under wave coupling conditions, and its accuracy and feasibility are validated. The results indicate that the proposed method improves the computational efficiency of hot spot stress by 4 to 5 orders of magnitude. Moreover, the accuracy of fatigue damage calculation is significantly improved compared to the traditional frequency band method, particularly under sea conditions with large spectral width coefficients. This method enables precise and efficient fatigue analysis of floating offshore wind turbines, making it suitable for rapid assessment of floating offshore wind turbine fatigue issues.
