• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Reliability Engineering & System Safety >Study on the systematic approach of Markov modeling for dependability analysis of complex fault-tolerant features with voting logics
【24h】

Study on the systematic approach of Markov modeling for dependability analysis of complex fault-tolerant features with voting logics

机译：用投票逻辑对复杂容错特征进行可靠性分析的马尔可夫建模系统方法研究

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The Markov analysis is a technique for modeling system state transitions and calculating the probability of reaching various system states. While it is a proper tool for modeling complex system designs involving timing, sequencing, repair, redundancy, and fault tolerance, as the complexity or size of the system increases, so does the number of states of interest, leading to difficulty in constructing and solving the Markov model. This paper introduces a systematic approach of Markov modeling to analyze the dependability of a complex fault-tolerant system. This method is based on the decomposition of the system into independent subsystem sets, and the system-level failure rate and the unavailability rate for the decomposed subsystems. A Markov model for the target system is easily constructed using the system-level failure and unavailability rates for the subsystems, which can be treated separately. This approach can decrease the number of states to consider simultaneously in the target system by building Markov models of the independent subsystems stage by stage, and results in an exact solution for the Markov model of the whole target system. To apply this method we construct a Markov model for the reactor protection system found in nuclear power plants, a system configured with four identical channels and various fault-tolerant architectures. The results show that the proposed method in this study treats the complex architecture of the system in an efficient manner using the merits of the Markov model, such as a time dependent analysis and a sequential process analysis. (C) 2016 Elsevier Ltd. All rights reserved.
机译：马尔可夫分析是一种用于对系统状态转换进行建模并计算达到各种系统状态的概率的技术。尽管它是用于对复杂的系统设计（包括时序，顺序，维修，冗余和容错）进行建模的合适工具，但是随着系统的复杂性或规模的增加，关注状态的数量也会增加，从而导致构造和求解上的困难马尔可夫模型。本文介绍了一种马尔可夫建模的系统方法来分析复杂容错系统的可靠性。此方法基于将系统分解为独立的子系统集，以及分解后的子系统的系统级故障率和不可用率。使用子系统的系统级故障率和不可用率，可以轻松构建目标系统的马尔可夫模型。通过逐步构建独立子系统的马尔可夫模型，该方法可以减少目标系统中同时考虑的状态数量，从而为整个目标系统的马尔可夫模型提供精确的解决方案。为了应用该方法，我们为核电厂中的反应堆保护系统构建了一个马尔可夫模型，该系统配置有四个相同的通道和各种容错架构。结果表明，本研究中提出的方法利用Markov模型的优点，如时变分析和顺序过程分析，有效地处理了系统的复杂体系结构。 （C）2016 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号