• DocumentCode
    615417
  • Title

    Fault diagnosis of the satellite power system based on the Bayesian network

  • Author

    Siyun Xie ; Xiafu Peng ; Xunyu Zhong ; Chengrui Liu

  • Author_Institution
    Dept. of Autom., Xiamen Univ., Xiamen, China
  • fYear
    2013
  • fDate
    26-28 April 2013
  • Firstpage
    1004
  • Lastpage
    1008
  • Abstract
    The satellite power system is an important piece of the satellite system; targeting on the problems of complex fault mechanisms and uncertainty between fault type and fault symptoms, the method of Bayesian network fault diagnosis in the satellite power system has been raised. In the learning process of Bayesian network structure, this algorithm adopts statistical strategy for the rule library provided by many experts, extracts causal relationship from expert knowledge base, fills in the causal relationship table, thereby sets up the fault diagnosis hierarchical structure model in the satellite power system based on Bayesian network. Simulation shows that the Bayesian network fault diagnosis model is effectively solving the uncertainties in fault diagnosis.
  • Keywords
    artificial satellites; belief networks; fault diagnosis; learning (artificial intelligence); power engineering computing; power system reliability; statistical analysis; Bayesian network; causal relationship table; fault diagnosis hierarchical structure model; fault mechanism; fault symptom; fault type; learning process; rule library; satellite power system; statistical strategy; Bayes methods; Laboratories; Topology; Voltage control; Bayesian network; fault diagnosis; satellite power system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education (ICCSE), 2013 8th International Conference on
  • Conference_Location
    Colombo
  • Print_ISBN
    978-1-4673-4464-7
  • Type

    conf

  • DOI
    10.1109/ICCSE.2013.6554060
  • Filename
    6554060