Volume 45 Issue 7
Jul.  2019
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SHI Xianjun, WANG Kang, XIAO Zhicai, et al. Three-dimensional Bayes network testability verification model for complex systems[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(7): 1303-1313. doi: 10.13700/j.bh.1001-5965.2018.0663(in Chinese)
Citation: SHI Xianjun, WANG Kang, XIAO Zhicai, et al. Three-dimensional Bayes network testability verification model for complex systems[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(7): 1303-1313. doi: 10.13700/j.bh.1001-5965.2018.0663(in Chinese)

Three-dimensional Bayes network testability verification model for complex systems

doi: 10.13700/j.bh.1001-5965.2018.0663
More Information
  • Corresponding author: SHI Xianjun, E-mail: sxjaa@sina.com
  • Received Date: 19 Nov 2018
  • Accepted Date: 02 Feb 2018
  • Publish Date: 20 Jul 2019
  • In view of the complicated system structure of current weapon equipment, the existing testability verification method based on the testability prior information of the equipment system is difficult to apply, and the testability verification method based on the testability prior information of the subsystem cannot process the prior information effectively, which lead to the low credibility of the testability verification results, so a three-dimensional Bayes network testability verification model for complex systems is proposed. The model can fully utilize the conditional independence contained in the various hierarchical structures of the equipment, effectively reduce the complexity of constructing the Bayesian network model, and at the same time integrate the prior information of each hierarchical unit. Through the given conditional probability learning method and G/M-H algorithm of the three-dimensional Bayes network, the underlying unit data can be integrated through the model to obtain the posterior distribution of the top-level testability indicators, and the top-level posterior distribution is further used to obtain the fault sample size. The results show that the model can fully consider the system structure of the complex system and the prior information of each hierarchical unit, and the posterior distribution of the testability indicators can be used to reduce the fault sample size of testability verification.

     

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