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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability >Multi-objective genetic algorithm for optimization of system safety and reliability based on IEC 61508 requirements: a practical approach
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Multi-objective genetic algorithm for optimization of system safety and reliability based on IEC 61508 requirements: a practical approach

机译:基于IEC 61508要求的用于优化系统安全性和可靠性的多目标遗传算法:一种实用方法

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摘要

This paper presents a practical approach for optimization by evolutionary computation of safety instrumented system design, based on safety and reliability measures, plus life cycle cost. The standard IEC 61508 establishes the necessity of this kind of systems to meet specific safety integrity requirements, expressed in terms of safety integrity levels (SIL). The SIL is determined in terms of average probability of failure on demand (PFDavg) for control systems that operate in demand mode. The optimization executed takes into account the level of modelling detail contemplated by the standard, including multiple failure modes, diagnostic coverage, and common cause failures. This study addresses the case of series-parallel systems. Optimization is approached by treating the problem as one of redundancy and reliability allocation, together with testing intervals specifications. Modelling is made through fault tree analysis with house events. The multi-objective genetic algorithm proposed by Fonseca and Fleming is used as the optimization technique.
机译:本文提出了一种实用的方法,该方法基于安全性和可靠性措施以及生命周期成本,通过对安全仪表系统设计进行进化计算来进行优化。 IEC 61508标准确立了此类系统满足特定安全完整性要求的必要性,以安全完整性级别(SIL)表示。 SIL是根据在按需模式下运行的控制系统的按需平均故障概率(PFD avg )确定的。执行的优化考虑了该标准考虑的建模细节级别,包括多种故障模式,诊断范围和常见原因故障。这项研究解决了串并联系统的情况。通过将问题视为冗余和可靠性分配之一以及测试间隔规范来实现优化。通过故障树分析和房屋事件进行建模。 Fonseca和Fleming提出的多目标遗传算法被用作优化技术。

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