• DocumentCode
    2468059
  • Title

    Simulation method of fault diagnosis tree evaluation

  • Author

    Shi, Junyou ; Lv, Kaiyue

  • Author_Institution
    Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Fault diagnosis tree based on dependency models is becoming an important way to improve testability. For the purpose of evaluation of a fault diagnosis tree, a simulation method of fault diagnosis tree evaluation is proposed, with which we can evaluate the real diagnosis capacity of a fault diagnosis tree. The principal of fault diagnosis tree evaluation is analyzed, with the tuple relation models of simulation established and the detailed simulation flow given. Evaluations of fault detection rate (FDR), fault isolation rate (FIR) can be made with this method. The main steps of this method include: 1) configure test thresholds, 2) obtain original test data, 3) convert original test data into logical test data, 4) simulate fault diagnosis tree and obtain diagnostic conclusions, 5) evaluate diagnosis capacity and give corresponding suggestions. Finally, a case of the signal conditioning circuit is given. Based on the method mentioned above, assistant software is developed and the simulation is made with test data in fault states, and the result shows that the method is feasible and effective.
  • Keywords
    decision trees; fault diagnosis; maintenance engineering; assistant software; configure test thresholds; dependency models; detailed simulation flow given; diagnosis capacity; diagnostic conclusions; fault detection rate evaluations; fault diagnosis tree evaluation simulation method; fault isolation rate; maintenance time; original test data; signal conditioning circuit; testability; tuple relation models; Fault diagnosis; Neodymium; dependency model; evaluation; fault diagnosis tree; simulation; test thresholds;
  • 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.2012.6228787
  • Filename
    6228787