针对海上浮式风机复杂的受荷环境，特别是持续、周期性的海浪作用带来的疲劳损伤隐患，对其在波浪耦合作用下的疲劳性能展开了研究，给出了一种浮式风机长期视角下的疲劳损伤评估方法。以Spar型海上浮式风机为对象，基于拉格朗日方程建立了其8-DOF（dgree of freedom）的波浪耦合作用非线性模型，并验证了所建模型的准确性，随后在所建模型基础上根据所提方法对其疲劳性能进行了探讨。结果表明，浮式风机的疲劳损伤与波浪载荷特性关系很大，不同工况下表现出不同的损伤性能，由于海况条件的随机性，仅按传统方法对风机进行疲劳估计不足以准确了解其疲劳性能，还需进行长期视角下的疲劳分析。而且风机塔架根部疲劳损伤的峰值出现在塔架自振周期附近，而长期疲劳损伤的峰值则出现在海域高概率海况周期范围，因此应尽量使风机的自振周期避开其峰值周期，从而避免风机损伤的高位叠加，减小疲劳损伤。分析还表明了所提基于蒙特卡洛法的浮式风机长期疲劳计算方法的有效性，精度高且耗时少，提出的改进算法能使输出结果波动变小、稳定性增强，结果也更为精确。

Considering the complex loading environment of the floating offshore wind turbine (FOWT), especially the fatigue damage risks brought by continuous and periodic wave actions, the fatigue performance of FOWT under wave coupling excitation was studied and a long-term fatigue damage assessment method for FOWT was proposed. Taking the Spar FOWT as an example, a nonlinear model under the wave coupling excitation of 8-DOF (dgree of freedom) was established based on the Lagrange equation, and the accuracy of the model was verified. Subsequently, on the basis of the established nonlinear model, the fatigue performance of the example FOWT was discussed according to the proposed method. The results indicate that the fatigue damage of FOWT is closely related to the wave load characteristics, and different damage performance is exhibited under different working conditions. Due to the randomness of sea conditions, only short-term fatigue estimation of the wind turbine is not enough to accurately understand its fatigue performance, and long-term fatigue analysis is needed. Moreover, the peak of short-term fatigue damage at the root of the wind turbine tower occurs near the tower's natural vibration period, while the peak of long-term fatigue damage occurs within the range of high probability sea state periods in the sea. Therefore, efforts should be made to avoid the natural vibration period of the FOWT coinciding with the peak period to prevent high-level damage accumulation and reduce fatigue damage. The analysis also demonstrates the effectiveness of the proposed Monte Carlo based long-term fatigue calculation method for FOWT, which not only has high accuracy but also less time consumption. The proposed improvement method can reduce output fluctuations, enhance stability, and provide more precise results.