A Bayesian network-based dynamic approximate weight wind turbine generator operation state comprehensive evaluation method

According to the Bayesian network-based dynamic approximate weight wind turbine generator running state comprehensive evaluation method, The method comprises steps of utilizing scada data to determinea wind turbine generator state evaluation parameter vector, and classifying wind turbine generator fault modes; And constructing a three-layer Bayesian network to describe the operation parameter vector of the wind turbine generator and the fault causal relationship, determining the prior distribution of the Bayesian network parameter vector, and determining the hyper-parameter of the product Dirichlet distribution through the experience knowledge of the wind turbine generator. And determining the posterior probability distribution of the Bayesian network parameters. And calculating conditional probability distribution of each node in the Bayesian network under different states of father nodes of the node. And comprehensively evaluating the operation state of the wind turbine generator according to the dynamic ap