The performance assessment of safety barriers is essential to find vulnerable elements in a safety barrier system. Traditional performance assessment approaches mainly focus on using several static indicators for quantifying the performance of safety barriers. However, with the increasing complexity of the system, emerging hazards are highly uncertain, making it challenging for the static indicators to assess the performance of safety barriers. This paper proposes a resilience−based performance assessment method for safety barriers to overcome this problem. Safety barriers are classified according to their functions first. The dynamic Bayesian network (DBN) is then introduced to calculate the availability function under normal and disruption conditions. The ratio of the system's availability, when affected by the disruption, to the initial availability, is used to determine the absorption capacity of the system. The ratio of the quantity of availability recovery to the total quantity of system represents the adaptation and restoration capacity of the system. The system's resilience is represented by the sum of absorption, adaptation, and restoration capacities. The wax oil hydrogenation process is used to demonstrate the applicability of the proposed methodology.

安全屏障的性能评估对于发现安全屏障系统中的脆弱元素至关重要。传统的性能评估方法主要侧重于使用几个静态指标来量化安全屏障的性能。然而，随着系统复杂性的增加，新出现的危害具有高度的不确定性，这使得静态指标评估安全屏障的性能具有挑战性。本文提出了一种基于弹性的安全屏障性能评估方法来克服这个问题。安全栅首先根据其功能进行分类。然后引入动态贝叶斯网络（DBN）来计算正常和中断条件下的可用性函数。系统可用性的比率，当受到中断影响时，初始可用性，用于确定系统的吸收能力。可用恢复量与系统总量的比值代表了系统的适应和恢复能力。系统的弹性由吸收、适应和恢复能力的总和来表示。蜡油加氢过程用于证明所提出方法的适用性。