Application of semi-Markov process and CTMC to evaluation of UPS system availability

Liang Yin, R. M. Fricks, Kishor S. Trivedi
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引用次数: 34

Abstract

In this paper, the authors develop analytical models for the study of the dependability characteristics of systems with uninterruptible power supply (UPS) units. Dependability of systems with UPS cannot be modeled exactly using the prevalent Markov modeling approaches. They develop and solve two approximations to this problem. The first model assumes that battery units will be fully recharged before the next failure occurs. With this assumption, a semi-Markov process (SMP) model is developed and solved to provide formulae to compute availability measures (transient and steady-state), reliability and mean time to failure (MTTF). Another approximation based only on Markov modeling theory is then proposed. The authors show how all the measures can also be computed using the continuous-time Markov chain (CTMC) approach, and also compare some of its results with the equations developed. In practical applications, the closed-form formulae for A(t), A and MTTF are very useful in combination with other system equations in a reliability block diagram or fault-tree. On the other hand, the Erlang approximation is easy to use when one has Markov chain solvers (e.g., the SPNP or SHARPE modeling packages) available for computing dependability measures.
半马尔可夫过程和CTMC在UPS系统可用性评价中的应用
本文建立了研究不间断电源(UPS)系统可靠性特性的分析模型。使用流行的马尔可夫建模方法不能精确地对UPS系统的可靠性进行建模。他们提出并解决了这个问题的两个近似。第一个模型假设电池单元在下一次故障发生之前将被完全充电。在此假设下,建立并求解了半马尔可夫过程(SMP)模型,提供了计算可用性指标(瞬态和稳态)、可靠性和平均故障时间(MTTF)的公式。然后提出了另一种仅基于马尔可夫建模理论的近似。作者展示了如何使用连续时间马尔可夫链(CTMC)方法计算所有度量,并将其结果与所开发的方程进行了比较。在实际应用中,A(t)、A和MTTF的封闭形式公式在与可靠性框图或故障树中的其他系统方程结合使用时非常有用。另一方面,当一个人有马尔可夫链求解器(例如,SPNP或SHARPE建模包)可用于计算可靠性度量时,Erlang近似很容易使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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