首页> 外文会议>22nd International Conference on Computer Safety, Reliability, and Security SAFECOMP 2003 Sep 23-26, 2003 Edinburgh, UK >Quantitative Reliability Estimation of a Computer-Based Motor Protection Relay Using Bayesian Networks
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Quantitative Reliability Estimation of a Computer-Based Motor Protection Relay Using Bayesian Networks

机译:贝叶斯网络的基于计算机的电动机保护继电器的定量可靠性估计

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A quantitative reliability estimation of a computer-based motor protection relay is presented. The evidence used for the estimation consists of expert judgements on the development process and estimated operational experience of the computer-based system. The framework of Bayesian modelling and Bayesian networks was applied throughout the assessment. A prior reliability estimation of the motor protection relay was built using the expert judgements on the product development process. The prior estimation was updated by taking into account the estimated operational experience for successive software versions. Prior estimations for possible reliability changes between different software versions were included to the assessment using the expert judgements on the version management of the motor protection relay. The Bayesian networks seem to provide an excellent way of performing quantitative reliability estimations of computer-based systems. Bayesian networks are particularly useful when different kinds of evidence is introduced and combined in the same assessment. The assessment method described in the paper gives informative posterior probability distributions for the failure rates of different software versions. The methodology can be used as a communicative tool between different participants debating on the reliability of a system and as a follow-up of reliability trend during the life cycle of a computer-based system.
机译:提出了基于计算机的电动机保护继电器的定量可靠性估计。用于估计的证据包括对基于计算机的系统的开发过程和估计的操作经验的专家判断。在整个评估中都采用了贝叶斯建模和贝叶斯网络框架。使用产品开发过程中的专家判断来建立电动机保护继电器的先前可靠性估计。通过考虑后续软件版本的估计操作经验来更新先前的估计。使用对电动机保护继电器的版本管理的专家判断,先前对不同软件版本之间可能的可靠性变化进行的估算已包括在评估中。贝叶斯网络似乎为执行基于计算机的系统的定量可靠性估计提供了一种极好的方法。当引入不同种类的证据并将其合并到同一评估中时,贝叶斯网络特别有用。本文中描述的评估方法给出了不同软件版本的故障率的有益的后验概率分布。该方法可以用作讨论系统可靠性的不同参与者之间的交流工具,并且可以用作基于计算机的系统生命周期中可靠性趋势的跟踪。

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