Measuring system reliability by a reasonable metric is a common problem in reliability engineering. Since real systems are usually uncertain random systems affected by both aleatory and epistemic uncertainties, existing reliability metrics are unreliable. This paper proposes a general reliability metric, called belief reliability metric, to cope with the problem. In this paper, the belief reliability is defined as the chance that a system state is within a feasible domain. Mathematically, the metric can degenerate to either probability theory-based reliability, which copes with aleatory uncertainty, or uncertainty theory-based reliability, which considers the effect of epistemic uncertainty. Based on the proposed metric, some commonly used belief reliability indexes, such as belief reliability distribution, mean time to failure, and belief reliable life, are introduced. We also develop system belief reliability formulas for different systems configurations. To further illustrate the formulas, a real case study is performed.

中文翻译：

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不确定随机系统的置信可靠性


通过合理的度量来衡量系统的可靠性是可靠性工程中的一个常见问题。由于真实系统通常是不确定的随机系统，受到偶然和认知不确定性的影响，现有的可靠性指标是不可靠的。本文提出了一种通用的可靠性度量，称为置信可靠性度量，来解决这个问题。在本文中，置信可靠性被定义为系统状态处于可行域内的机会。从数学上讲，该度量可以退化为基于概率论的可靠性（处理偶然的​​不确定性）或基于不确定性理论的可靠性（考虑认知不确定性的影响）。基于所提出的度量，介绍了一些常用的信念可靠性指标，例如信念可靠性分布、平均无故障时间和信念可靠寿命。我们还为不同的系统配置开发系统信念可靠性公式。为了进一步说明这些公式，进行了一个真实的案例研究。