• DocumentCode
    2302562
  • Title

    Residual-Life Prediction for Civil Aviation Engines Based on Wiener-Einstein Process

  • Author

    Shuhong, Ren ; Hongfu, Zuo

  • Author_Institution
    Civil Aviation Coll., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    415
  • Lastpage
    419
  • Abstract
    This paper makes study of the civil aviation aircraft engine. Real-time condition monitoring is becoming an important tool in maintenance decision-making. To make effective use of condition information, it is useful to characterize a device degradation signal, a quantity computed from condition information that captures the current state of the device and provides information on how that condition is likely to evolve in the future. In this paper, we develop the residual-life prediction method to current degradation signals by using the characteristic of Wiener-Einstein Process. We apply these degradation and residual-life models to degradation signals obtained through the PW4000 engine fleet application in an airline. The result illustrates the precision and validity of this method which could support the engine CBM decision-making.
  • Keywords
    aerospace engines; aircraft maintenance; condition monitoring; decision making; stochastic processes; PW4000 engine fleet application; Wiener-Einstein process; civil aviation aircraft engine; condition information; device degradation signal; maintenance decision-making; real-time condition monitoring; residual-life prediction; Aircraft propulsion; Condition monitoring; Decision making; Degradation; Educational institutions; Engines; Life estimation; Software engineering; Stochastic processes; Stress; Wiener-Einstein Process; reliability; residual-life prediction; the civil aviation aircraft engine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, 2009. WCSE '09. WRI World Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3570-8
  • Type

    conf

  • DOI
    10.1109/WCSE.2009.58
  • Filename
    5319440