基于半马尔科夫决策过程的风力机状态维修优化  

Condition-based Maintenance Optimization for Wind Turbines Based on Semi-Markov Decision Process

作　　者：苏春[1] 周小荃[1] 

机构地区：[1]东南大学机械工程学院,南京211189

出　　处：《机械工程学报》2012年第2期44-49,共6页Journal of Mechanical Engineering

基　　金：国家自然科学基金资助项目(50405021)

摘　　要：恶劣的工作环境、昂贵的维修成本和停机损失对风力机及其部件的维修提出挑战。以齿轮箱、叶片等风力机核心机械部件为对象,将部件退化过程离散成有限的退化状态;以长期折扣成本最低为目标,考虑风速、备件物流、停机损失等因素的影响,建立基于半马尔科夫决策过程的状态维修优化模型。分析各退化状态下的维修策略、检测间隔时间以及不同退化状态间的转移概率,并采用策略迭代算法求解模型。以某风力机齿轮箱为例,通过对等周期、非等周期检测条件下检测间隔时间和维修成本的分析,得到优化的维修决策。研究结果表明,该模型能有效描述风力机核心部件的退化过程,实现风力机维修优化。Tough working environment,expensive maintenance cost and production losses have put forward significant challenge to the maintenance of wind turbine and its components.The key components in the wind turbine such as gearbox and blade are selected as the object of study,the degradation process is divided into finite degradation states.With the objective of minimizing long-term discount cost,the critical factors including wind speed,spare parts logistics and production losses are taken into account,and a condition-based maintenance optimization model is established which is based on the semi-Markov decision process.The maintenance policy,the inspection interval under each state,and the transition probabilities between different states are analyzed,and the model is solved with the method of policy iteration.The proposed approach is applied to a wind turbine gearbox,by way of analyzing the inspection interval and maintenance cost under periodical inspection and non-periodical inspection,the optimal maintenance policies are obtained.The result shows the presented model can describe the degradation process effectively,and can be used to optimize the maintenance policies.

关 键 词：风力机 半马尔科夫决策过程 状态维修 策略迭代 

分 类 号：TG156[金属学及工艺—热处理]