为了提高风机运行的可靠性和经济性,提出一种基于马尔科夫链的风机齿轮箱轴承状态评估和剩余寿命预测方法.首先,建立风机齿轮箱轴承磨损状态的Gamma分布模型,并利用最大似然法对模型参数进行估计;其次,划分风机齿轮箱轴承磨损状态等级,并确定各状态等级区间限值;再次,计算齿轮箱轴承磨损状态转移概率,并构造马尔科夫过程的状态转移矩阵;最后,应用该方法对风机齿轮箱轴承进行算例仿真.算例仿真结果验证了该方法在确定风机齿轮箱轴承磨损状态和剩余寿命方面的有效性.%In order to improve reliability and economy of wind turbine,a method based on Markov chain is proposed.It is used for assessing operating condition and predicting residual life of gearbox bearing of wind turbine.Firstly,the degradation process of bearing wear status is described by Gamma distribution whose parameters can be estimated by using maximum likelihood estimation method.Secondly,the wear status of gearbox bearing are divided into four levels,and the corresponding upper and lower bounds of each level are also determined.Then,state transition probabilities are calculated to construct the state transition matrix.Finally,the proposed method is applied in simulation of wind turbine gearbox bearing.The simulation result verifies the effectiveness of presented method in determining the wear state and residual life of gearbox bearing of wind turbine.
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