• DocumentCode
    183775
  • Title

    Failure prognosability of stochastic discrete event systems

  • Author

    Jun Chen ; Kumar, Ravindra

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    2041
  • Lastpage
    2046
  • Abstract
    We study the prognosis of fault, i.e., its prediction prior to its occurrence, in stochastic discrete event systems. We introduce the notion of m-steps Stochastic-Prognosability, called Sm-Prognosability, which allows the prediction of a fault at least m-steps in advance. We formalize the notion of a prognoser and also show that Sm-Prognosability is necessary and sufficient for the existence of a prognoser that can predict a fault at least m-steps prior to occurrence, while achieving any arbitrary false alarm and missed detection rates. We also provide a polynomial algorithm for the verification of Sm-Prognosability.
  • Keywords
    discrete event systems; failure analysis; fault diagnosis; polynomials; stochastic systems; Sm-prognosability; failure prognosability; false alarm; fault prediction; fault prognosis; m-steps stochastic-prognosability; missed detection rates; polynomial algorithm; prognoser; stochastic discrete event systems; Automata; Delays; Discrete-event systems; Polynomials; Prognostics and health management; Stochastic processes; Automata; Discrete event systems; Fault detection/accommodation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6858775
  • Filename
    6858775