海上风电场运行环境恶劣、维修船只出海成本高，因而海上风电机组的维修通常集中进行，这对于海上风电机组部件的备件库存管理提出了更高的要求。为此，提出了一种综合考虑部件退化状态的视情维护与备件库存管理的集成策略，显著减少了风电机组失效时长，降低了停机损失。以海上风电机组的巡检周期、部件的维修阈值与备件管理的再订货点、订货批量为联合决策变量，以系统的成本率为目标函数建立数学模型。针对模型中的随机变量和维护与备件库存管理的耦合关系导致的高度复杂性，设计蒙特卡洛仿真算法估计其目标函数值。最后通过仿真实验进行灵敏度分析，验证了本文所提模型的有效性。

Maintenance activities of offshore wind turbines are usually centralized due to the severe weather and expensive sailing cost, which puts forward higher requirements for the spare parts inventory management of offshore wind turbine components. Based on this problem, this paper presents an integrated model for condition-based maintenance and spare parts management. It significantly reduces the failure time of the wind turbine and reduces the shutdown loss. Taking the inspection cycle of offshore wind turbine, the maintenance threshold of components, the reorder point and the order quantity of spare parts as the joint decision variables, a mathematical model with the objective of minimization of cost rate is established. Due to the high complexity resulting from random variables as well as coupling relationship between maintenance and spare parts management, Monte Carlo simulation algorithm is designed to estimate the objective value of the model. Finally, the simulation based sensitive analysis experiment shows the effectiveness of the proposed model and algorithm.