• DocumentCode
    2121517
  • Title

    Linear independent increment process with linear standard deviation function for degradation analysis

  • Author

    Zhihua Wang ; Huimin Fu ; Yongbo Zhang

  • Author_Institution
    Res. Center of Small Sample Technol., Beihang Univ., Beijing, China
  • fYear
    2013
  • fDate
    15-19 Jan. 2013
  • Firstpage
    94
  • Lastpage
    98
  • Abstract
    Degradation test is a feasible means to assess the failure time distributions of complex systems and highly reliable products. Generally speaking, the degradation process is essentially a continuous state random process. Motivated by the independent increment process theory, we propose a degradation analysis model, in which degradation is represented by an independent increment process with linear mean and standard deviation functions (quadratic variance function). A one-stage method is further developed to estimate the model parameters and failure time distribution. The methodology has been implemented in the analysis of GaAs laser degradation. The comparative results illustrate that the proposed method can be considered good and show a promise for future applications.
  • Keywords
    random processes; reliability theory; statistical analysis; complex system; continuous state random process; degradation analysis model; degradation process; degradation test; failure time distribution; laser degradation; linear independent increment process theory; linear mean deviation function; linear standard deviation function; model parameter; quadratic variance function; reliable product; Degradation; Reliability; Degradation modeling; Failure time distribution; Life prediction; Linear independent increment process; Reliability assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Sciences and Technology (IBCAST), 2013 10th International Bhurban Conference on
  • Conference_Location
    Islamabad
  • Print_ISBN
    978-1-4673-4425-8
  • Type

    conf

  • DOI
    10.1109/IBCAST.2013.6512137
  • Filename
    6512137