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Improving fault diagnosis accuracy by automatic test set modification

机译:通过自动测试集修改来提高故障诊断的准确性

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Fault diagnosis is the task of identifying a faulty component in a complex system using data collecting from a test section. Diagnostic resolution, that is the ability to discriminate a faulty component in a set of possible candidates, is a property that the system model must expose to provide accuracy and robustness in the diagnosis. Such a property depends on the selection of an appropriate test set capable to provide a unique interpretation of the test outcomes. In this paper a quantitative metric for the evaluation of diagnostic resolution of a test set is proposed, together with an algorithm for the minimal extension of a given test set in order to provide a complete discrimination of failures affecting a system, to be used as a support for analysts during the definition of a testing framework.
机译:故障诊断是使用从测试部分收集的数据识别复杂系统中的故障组件的任务。诊断分辨率,即能够在一组可能的候选中区分故障组件,是系统模型必须暴露在诊断中提供准确性和鲁棒性的财产。这样的财产取决于选择适当的测试集,能够提供对测试结果的独特解释。在本文中,提出了评估测试集的诊断分辨率的定量度量,以及用于给定测试集的最小延伸的算法,以便提供影响系统的故障的完全辨别,用作在测试框架定义期间支持分析师。

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