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System reliability based on diffusion models for fatigue crack growth

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  • Nader Ebrahimi

Abstract

Diffusion processes are commonly used to describe the dynamics of complex systems arising in a wide range of application fields. In this paper we propose, on the basis of diffusion processes, two models concerned with the stochastic behavior of fatigue cracks in a system. They are then used to get the distribution of the failure time, the first time the crack size of at least one of the cracks exceeds a given value. Several properties of our proposed models are presented, and the unknown parameters are estimated by the method of maximum likelihood. From these an estimate of failure time distribution is obtained. In this part, contrary to common practice, we do not assume availability of failure data. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005

Suggested Citation

  • Nader Ebrahimi, 2005. "System reliability based on diffusion models for fatigue crack growth," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(1), pages 46-57, February.
    • Handle: RePEc:wly:navres:v:52:y:2005:i:1:p:46-57
    DOI: 10.1002/nav.20050
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    References listed on IDEAS

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    1. W. J. Padgett & S. D. Durham, 1989. "A model for critical crack size estimation in fatigue failure of gun barrels," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(2), pages 139-145, April.
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    Cited by:

    1. Jen Tang & Tsui‐Shu Su, 2008. "Estimating failure time distribution and its parameters based on intermediate data from a Wiener degradation model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(3), pages 265-276, April.
    2. Yin Shu & Qianmei Feng & David W. Coit, 2015. "Life distribution analysis based on Lévy subordinators for degradation with random jumps," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(6), pages 483-492, September.
    3. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.

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