Unbiased Variance Estimates for System Reliability Estimate Using Block Decompositions
Unbiased Variance Estimates for System Reliability Estimate Using Block Decompositions
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DOI：
10.1109/tr.2008.927809
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发表时间：
2008-08
影响因子：
5.9
通讯作者：
T. Jin;D. Coit
中科院分区：
文献类型：
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作者：
T. Jin;D. Coit
提出了一种基于部件可靠性估计方差估计的无偏估计量来计算系统可靠性估计方差。该方法不需要对组件可靠性或故障时间进行任何参数假设，并且它允许i型和ii型屏蔽数据。这种方法可以适用于许多情况，只要系统可以适当地分解为串联或并联配置。利用不同的可靠性数据和系统结构，将新模型与现有方法进行了比较。实证结果表明，新模型在计算效率和估计精度方面总体上具有优势。
An unbiased estimator is proposed to calculate the variance of a system reliability estimate based on the estimated variance of component reliability estimates. The method does not require any parametric assumptions for component reliability or time-to-failure, and it allows Type-I and Type-II censored data. The approach can be applied to many situations as long as the system can be appropriately decomposed into series or parallel configurations. The new model is compared with existing methods using different reliability data and system structures. The empirical results show that the new model is generally superior in terms of computational efficiency, and estimation accuracy.