• DocumentCode
    693035
  • Title

    The information-enhanced BIT design of avionics system based on fuzzy neural network

  • Author

    Yao Guo-Ping ; Hou Wen-Kui ; Shi Long ; Shi Jun-You

  • Author_Institution
    Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
  • fYear
    2013
  • fDate
    20-22 Dec. 2013
  • Firstpage
    2950
  • Lastpage
    2954
  • Abstract
    Based on the needs of current avionics system fault diagnosis and health management on engineering project, this paper designed a program for fault diagnosis of typical avionics system module based on artificial intelligence. The basic principle of information-enhanced BIT was discussed. Then a fuzzy nature network designed for fault was built which combined self-adaption function. Beside software and hardware diagnosis overall framework is included. This paper provided a strong support for improving the ability of fault diagnosis of avionics products, reducing false alarms.
  • Keywords
    artificial intelligence; avionics; built-in self test; fault diagnosis; fuzzy neural nets; artificial intelligence; avionics system; fault diagnosis; fuzzy neural network; hardware diagnosis; health management; information-enhanced BIT design; software diagnosis; Aerospace electronics; Biological neural networks; Fault diagnosis; Fuzzy neural networks; Knowledge engineering; Training; BIT(built-in test); avionics system; fault diagnosis; fuzzy nature network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
  • Conference_Location
    Shengyang
  • Print_ISBN
    978-1-4799-2564-3
  • Type

    conf

  • DOI
    10.1109/MEC.2013.6885535
  • Filename
    6885535