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SBT soft fault diagnosis in analog electronic circuits: a sensitivity-based approach by randomized algorithms

机译:模拟电子电路中的SBT软故障诊断:基于敏感性的随机算法

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This paper addresses the fault diagnosis issue based on a simulation before test philosophy in analog electronic circuits. Diagnosis, obtained by comparing signatures measured at the test nodes with those contained in a fault dictionary, allows for sub-systems testing and fault isolation within the circuit. A novel method for constructing the fault dictionary under the single faulty component/unit hypothesis is proposed. The method, based on a harmonic analysis, allows for selecting the most suitable test input stimuli and nodes by means of a global sensitivity approach efficiently carried out by randomized algorithms. Applicability of the method to a wide class of circuits and its integration in diagnosis tools are granted since randomized algorithms assure that the selection problem can be effectively carried out with a poly-time algorithm independently from the fault space, structure, and complexity of the circuit.
机译:本文基于模拟电子电路中的测试前仿真原理,解决了故障诊断问题。通过将在测试节点处测得的签名与故障字典中包含的签名进行比较,可以进行诊断,从而可以对子系统进行测试并在电路内进行故障隔离。提出了一种在单一故障分量/单位假设下构造故障字典的新方法。该方法基于谐波分析,允许通过由随机算法有效执行的全局灵敏度方法来选择最合适的测试输入激励和节点。该方法适用于广泛的电路,并已集成到诊断工具中,因为随机算法可确保选择问题可以通过多重时间算法有效地执行,而不受故障空间,结构和电路复杂性的影响。

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