• DocumentCode
    2471747
  • Title

    Complex system fault sampling under condition of imperfect repair

  • Author

    Zhang, Chao ; Guo, Linhan ; Xiao, Boping ; Kang, Rui

  • Author_Institution
    Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    When complex system corrective maintenance activities are simulated, product fault occasion occurrences are usually simulated by random sampling method to impel corrective maintenance activity simulation to run. Product fault is usually sampled stochastically under complete repair or minimum repair condition in present research, but the product is usually repaired under imperfect repair condition in real world. In order to enhance the simulation model credibility product fault stochastic sampling method based on the arbitrary distribution is proposed under imperfect repair condition, where product failure rates are time-variant. Top-down and down-top failure sampling model is established to each layer product in the complex system, and the model applicability is analyzed. Finally a product fault sampling example according to the top-down method is constructed under imperfect repair conditions It can be concluded that the proposed methodology is of high validity and feasibility in this paper.
  • Keywords
    condition monitoring; failure analysis; large-scale systems; maintenance engineering; random processes; sampling methods; stochastic processes; complex system fault sampling; corrective maintenance activity simulation model credibility; down-top failure sampling model; imperfect repair condition; model applicability; product failure rate; product fault occasion occurrences; product fault stochastic sampling method; random sampling method; top-down failure sampling model; Computer aided software engineering; Silicon; fault sampling; imperfect repair; monte carlo;
  • 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.2012.6228962
  • Filename
    6228962