• DocumentCode
    3777348
  • Title

    Artificial intelligence and learning techniques in intelligent fault diagnosis

  • Author

    Sun Yuanyuan; Guo Lili; Wang Yongming

  • Author_Institution
    Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094 China
  • Volume
    1
  • fYear
    2015
  • Firstpage
    702
  • Lastpage
    707
  • Abstract
    At present, based on computer and information technology, intelligent diagnosis technology is in rapid development. In this paper, the application of artificial intelligence and learning techniques in intelligent fault diagnosis are demonstrated, such as Rule-Based Reasoning, Case-based Reasoning, Network neural, Fuzzy Logic, Genetic algorithm, Rough set theory, Bayesian network theory, Multi-agents, Reinforcement Learning, Support Vector Machine. Some kinds of applications are introduced. These intelligent fault diagnosis methods are widely used in complex fault diagnosis system. We will try to use them in our future intelligent fault diagnosis system for space station.
  • Keywords
    "Fault diagnosis","Genetic algorithms","Bayes methods","Cognition","Artificial neural networks","Biological neural networks","Fuzzy logic"
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2015 4th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2015.7490841
  • Filename
    7490841