Test equipment diagnosis based on fault tree and Bayesian network

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To ensure the high safety operation of test equipment and improve the diagnosis accuracy, this paper proposes a fusion fault diagnosis method based on the fault tree (FT) and Bayesian network (BN) model. To achieve a more comprehensive and in-depth diagnosis, and adapt to the characteristics of less fault data of the test equipment, the advantages of the FT and BN model are fully demonstrated to yield a combination results of qualitative and quantitative. Finally, the correctness and validity of the proposed model are verified by using a typical test equipment model.