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Variance and Approximate Confidence Limits for Probability and Frequency of System Failure

机译:系统故障概率和频率的方差和近似置信极限

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Two different types of approximation account for the effect of uncertain component failure and repair rates on the probability and the frequency of failure of repairable systems: 1. Use the orthodox statistical procedure of characterizing distributions by their low order moments and then use the conservative Chebyshev inequality to bound the probabilities so that the random variables lie within a certain range. 2. Apply Monte Carlo simulation based on common probability models, with which component test data can be translated into approximate system reliability limits at any s-confidence level. The two types are compared by an example. The performance of both types improve with the sample size of component data, but bounds from the Chebyshev inequality are wider than those obtained from Monte Carlo simulation. Both approaches represent the system by minimal cut-sets. The algorithms are intended for digital-computer implementation; computational times are provided.
机译:两种不同类型的近似值说明了不确定的组件故障和修复率对可修复系统的概率和失败频率的影响:1.使用正统统计程序通过低阶矩表征分布,然后使用保守的Chebyshev不等式限制概率,使随机变量处于一定范围内。 2.基于常见概率模型应用蒙特卡洛模拟,使用该模型可以将组件测试数据转换为任何s置信度级别的近似系统可靠性极限。通过示例比较这两种类型。两种类型的性能都随组件数据的样本大小而提高,但是Chebyshev不等式的界限比从Monte Carlo模拟获得的界限更宽。两种方法都以最小割集表示系统。该算法旨在用于数字计算机的实现;提供了计算时间。

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