• DocumentCode
    2210842
  • Title

    Dynamic modeling of degradation data

  • Author

    Jiang, Mingxiao ; Zhang, Yongcang

  • Author_Institution
    GE Corporate R&D, Niskayuna, NY, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    607
  • Lastpage
    611
  • Abstract
    In applications with few or no failures, degradation data can provide more reliability information than traditional censored failure-time data. In this paper, the authors present a dynamic model of degradation data comparing to the general ones available in literature. Random fatigue crack growth is illustrated in detail as an example of degradation data problem. The proposed model is ready to be generalized to accelerated life testing (ALT) analysis under various testing conditions
  • Keywords
    failure analysis; fatigue cracks; reliability; accelerated life testing; degradation data; degradation data dynamic modeling; failure analysis; random fatigue crack growth; reliability information; testing conditions; Data analysis; Failure analysis; Fatigue; Life estimation; Life testing; Markov processes; Research and development; Stochastic processes; Thermal degradation; Thermal stresses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability Symposium, 2002. Proceedings. Annual
  • Conference_Location
    Seattle, WA
  • ISSN
    0149-144X
  • Print_ISBN
    0-7803-7348-0
  • Type

    conf

  • DOI
    10.1109/RAMS.2002.981709
  • Filename
    981709