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Research on Fault Diagnosis of Steam Turbine Based on Bayesian Network

In the fault diagnosis of steam turbine, multiple faults contain number of uncertainties due to the complexity of fault diagnosis knowledge and the strong correlation and coupling between different faults and massive prior knowledge is needed. In this paper, a fault diagnosis method of steam turbine based on Bayesian network is proposed. Various faults and symptoms are parameterized using Bayesian network nodes. Then rough set theory is used to simplify the complex causal relationship between faults and symptoms, and Noisy-Or model is used to simplify the conditional probability parameters. A diagnostic model of the steam turbine was developed using a simplified Bayesian network. The experiment results are shown to validate the practicality and effectiveness of the proposed designs.