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Robustness of syndrome analysis method in highly structured fault-diagnosis systems

机译:高度结构化故障诊断系统中综合症分析方法的鲁棒性

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F. P. Preparata et al. proposed a fault diagnosis model (PMC model) to find all fault units in the multicomputer system by using outcomes that each unit tests some other units. T. Kohda proposed a highly structured(HS) system and the syndrome analysis method(SAM) to diagnose from local testing results. In this paper, we introduce the maximum a posteriori probability algorithm(MAPDA) for the HS system in the probabilistic fault model. Analyzing the MAPDA, we show that the SAM is closer to the MAPDA as the fault probability becomes smaller. Finally, we show the robustness of the SAM in the HS system.
机译:F.P.Preparata等。提出了一种故障诊断模型(PMC模型),以通过使用每个单元测试其他单元的结果来找到多计算机系统中的所有故障单元。 T. Kohda提出了一种高度结构化的(HS)系统和综合症分析方法(SAM),以根据本地测试结果进行诊断。本文介绍了概率故障模型中HS系统的最大后验概率算法(MAPDA)。分析MAPDA,我们发现随着故障概率变小,SAM更加靠近MAPDA。最后,我们展示了HS系统中SAM的鲁棒性。

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