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Bayesian network is an improtant variety of probability statistics,Because of its powerful capabilities of dealing with the uncertainty problem,it is suitable for diagnosis of complex system.The maintenance cost of wind turbine is very high,people needs to locate the faults accurately to reduce the maintenance cost. This paper studied the method of diagnosis based on bayesian network,described the details of the method for building the bayesian network diagnosis model ,especially for the derivation and calculaiton.It built the bayesian network MATLAB model of wind turbine using the historical fault data,this model contains Directed acyclic graph and Conditional probability distribution. Finally,this paper simulated two kinds of faults in the wind turbine system,two methods were used to diagnose these fault,One is the Bayesian network model and the other is the Dependency matrix.The result is that the Bayesian network method has the better fault resolution more than the Dependency matrix method,this could provides strong support to reducing maintenance cost of the complex system .