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Inventi Impact - Engineering Mathematics

Articles

  • Inventi:eem/61/14
    A DATA-DRIVEN RELIABILITY ESTIMATION APPROACH FOR PHASED-MISSION SYSTEMS
    Hua-Feng He, Juan Li, Qing-Hua Zhang, Guoxi Sun

    We attempt to address the issues associated with reliability estimation for phased-mission systems (PMS) and present a novel datadriven approach to achieve reliability estimation for PMS using the condition monitoring information and degradation data of such system under dynamic operating scenario. In this sense, this paper differs from the existing methods only considering the static scenario without using the real-time information, which aims to estimate the reliability for a population but not for an individual. In the presented approach, to establish a linkage between the historical data and real-time information of the individual PMS,we adopt a stochastic filtering model to model the phase duration and obtain the updated estimation of the mission time by Bayesian law at each phase. At themeanwhile, the lifetime of PMS is estimated fromdegradation data, which are modeled by an adaptive Brownian motion. As such, themission reliability can be real time obtained through the estimated distribution of the mission time in conjunction with the estimated lifetime distribution.We demonstrate the usefulness of the developed approach via a numerical example.

    How to Cite this Article
    CC Compliant Citation: Hua-Feng He, Juan Li, Qing-Hua Zhang, and Guoxi Sun, “A Data-Driven Reliability Estimation Approach for Phased- Mission Systems,” Mathematical Problems in Engineering, vol. 2014, Article ID 283740, 13 pages, 2014. doi:10.1155/2014/283740. Copyright © 2014 Hua-Feng He et al. This article is distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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