• DocumentCode
    3169101
  • Title

    Fault diagnosis method for HUD based on fuzzy BP neural network

  • Author

    Huang Lei ; Jian-guo, Nan ; Yong-hua, Sui ; Guo Lei ; Xue-feng, Wang

  • Author_Institution
    Dept. of Autom., Northwest Polytech. Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    29-30 Oct. 2010
  • Firstpage
    550
  • Lastpage
    553
  • Abstract
    For the insufficiency of the Built-in-test-equipment (BITE) of HUD and the ground fault diagnosis equipment, this paper provides a novel fault diagnosis based on fuzzy BP neural network for a certain type HUD by researching the fault diagnosis theory and methods. The proposed method simplifies the structure of the fault diagnosis system, and has a farther effective distinguish from the source of fault diagnosed by Built-in-test-equipment, and isolates the fault from the LRU level to the SRU level. Finally, the fault diagnosis example is provided with the typical test item. Experiments show that the proposed method shows better performance in fault diagnosis for HUD.
  • Keywords
    backpropagation; built-in self test; fault diagnosis; fuzzy neural nets; head-up displays; HUD; built in test equipment; fault diagnosis method; fuzzy BP neural network; head up display; Anodes; Fuzzy Neural Network; HUD; Knowledge-base; fault diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Education (ICAIE), 2010 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-6935-2
  • Type

    conf

  • DOI
    10.1109/ICAIE.2010.5641101
  • Filename
    5641101