在组件和系统级别上相干系统的关联冗余

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Chen Li, Xiaohui Li
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引用次数: 1

摘要

近年来,关联转换得到了研究者的进一步关注,并产生了一些有趣的结果。众所周知,组件级的主动冗余比系统级的主动冗余能产生更可靠的相干系统。然而,由于缺乏对关联冗余问题的研究,使我们无法充分理解主动冗余的这种泛化。在这篇笔记中,我们处理同质成分的相干系统的关联冗余。通常,对于独立组件的系列系统,我们分别在通常的随机顺序和似然比顺序下证明了组件级关联冗余系统的寿命大于系统级关联冗余系统的寿命。对于具有相关组件的相干系统,我们给出了控制函数在组件级冗余系统寿命与系统级冗余系统寿命之间的通常随机顺序的充分条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Relevation redundancy to coherent systems at component and system levels
Recently, the relevation transformation has received further attention from researchers, and some interesting results have been developed. It is well known that the active redundancy at component level results in a more reliable coherent system than that at system level. However, the lack of study of this problem with relevation redundancy prevents us from fully understanding such a generalization of the active redundancy. In this note we deal with relevation redundancy to coherent systems of homogeneous components. Typically, for a series system of independent components, we have proved that the lifetime of a system with relevation redundancy at component level is larger than that with relevation redundancy at system level in the sense of the usual stochastic order and the likelihood ratio order, respectively. For a coherent system with dependent components, we have developed a sufficient condition in terms of the domination function to the usual stochastic order between the system lifetime with redundancy at component level and that at system level.
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来源期刊
Journal of Applied Probability
Journal of Applied Probability 数学-统计学与概率论
CiteScore
1.50
自引率
10.00%
发文量
92
审稿时长
6-12 weeks
期刊介绍: Journal of Applied Probability is the oldest journal devoted to the publication of research in the field of applied probability. It is an international journal published by the Applied Probability Trust, and it serves as a companion publication to the Advances in Applied Probability. Its wide audience includes leading researchers across the entire spectrum of applied probability, including biosciences applications, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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