• DocumentCode
    2469143
  • Title

    Research on remote fault diagnosis task decomposition and decision approach

  • Author

    Guohua Wang ; Junjie Li

  • Author_Institution
    Sch. of Instrum. Sci. & Opto-Electron. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Diagnosis task decomposition and results decision fusion are important issues in the process of remote fault diagnosis (RFD) for aircraft. In order to solve the problem, this paper presents the task decomposition and decision fusion method based on fault tree model. First, the diagnosis task is decomposed according to the fault tree minimal cut sets and diagnosed by the remote diagnosis resources. Then Dempster-Shafer (D-S) evidential theory is applied to the diagnosis results to make decision fusion. A case study for an avionics system is shown to demonstrate the diagnosis decomposition and result decision fusion process, which shows that the proposed method is effective and improves the RFD reliability.
  • Keywords
    aircraft; condition monitoring; fault diagnosis; fault trees; D-S evidential theory; Dempster-Shafer evidential theory; RFD reliability; aircraft; avionics system; diagnosis results decision fusion process; fault tree minimal cut sets; fault tree model; remote diagnosis resources; remote fault diagnosis; task decomposition; Aerospace electronics; Reliability; Uncertainty; D-S evidential theory; Fault tree; Remote fault diagnosis; decision fusion; minimal cut set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and System Health Management (PHM), 2012 IEEE Conference on
  • Conference_Location
    Beijing
  • ISSN
    2166-563X
  • Print_ISBN
    978-1-4577-1909-7
  • Electronic_ISBN
    2166-563X
  • Type

    conf

  • DOI
    10.1109/PHM.2012.6228841
  • Filename
    6228841