Automatic generation of stimuli for fault diagnosis in IEEE 1687 networks

R. Cantoro, Mehrdad Montazeri, M. Reorda, Farrokh Ghani Zadegan, E. Larsson
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引用次数: 12

Abstract

The IEEE 1687 standard describes reconfigurable structures allowing to flexibly access the instruments existing within devices (e.g., to support test, debug, calibration, etc.), by the use of configurable modules acting as controllable switches. The increasing adoption of this standard requires the availability of algorithms and tools to automate its usage. Since the resulting networks could inevitably be affected by defects which may prevent their correct usage, solutions allowing not only to test against these defects, but also to diagnose them (i.e., to identify the location of possible faults) are of uttermost importance. This paper proposes a method to automatically generate suitable test stimuli: by applying them and observing the output of the network one can not only detect possible faults, but also identify the fault responsible for the misbehavior. Experimental results gathered on a set of benchmark networks with a prototypical tool implementing the proposed techniques show the feasibility and provide a first idea about the length of the required input stimuli.
IEEE 1687网络故障诊断的自动生成激励
IEEE 1687标准描述了可重构结构,通过使用可配置模块作为可控开关,允许灵活地访问设备内现有的仪器(例如,支持测试,调试,校准等)。越来越多地采用该标准需要可用的算法和工具来自动化其使用。由于最终的网络不可避免地会受到缺陷的影响,这可能会阻止它们的正确使用,因此解决方案不仅要允许对这些缺陷进行测试,而且还要允许对它们进行诊断(即,确定可能的故障的位置),这是极其重要的。本文提出了一种自动生成合适的测试刺激的方法:通过应用这些刺激并观察网络的输出,不仅可以检测到可能的故障,还可以识别导致异常行为的故障。使用原型工具在一组基准网络上收集的实验结果显示了可行性,并提供了所需输入刺激长度的初步想法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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