首页> 外文期刊>International Journal of Applied Mathematics and Computer Science >AUTOMATIC PARAMETRIC FAULT DETECTION IN COMPLEX ANALOG SYSTEMS BASED ON A METHOD OF MINIMUM NODE SELECTION
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AUTOMATIC PARAMETRIC FAULT DETECTION IN COMPLEX ANALOG SYSTEMS BASED ON A METHOD OF MINIMUM NODE SELECTION

机译:基于最小节点选择方法的复杂模拟系统中的参数故障自动检测

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The aim of this paper is to introduce a strategy to find a minimal set of test nodes for diagnostics of complex analog systems with single parametric faults using the support vector machine (SVM) classifier as a fault locator. The results of diagnostics of a video amplifier and a low-pass filter using tabu search along with genetic algorithms (GAs) as node selectors in conjunction with the SVM fault classifier are presented. General principles of the diagnostic procedure are first introduced, and then the proposed approach is discussed in detail. Diagnostic results confirm the usefulness of the method and its computational requirements. Conclusions on its wider applicability are provided as well.
机译:本文的目的是介绍一种策略,该方法使用支持向量机(SVM)分类器作为故障定位器,找到用于诊断具有单个参数故障的复杂模拟系统的最小测试节点集。给出了使用禁忌搜索以及遗传算法(GA)作为节点选择器以及SVM故障分类器对视频放大器和低通滤波器进行诊断的结果。首先介绍了诊断过程的一般原理,然后详细讨论了所提出的方法。诊断结果证实了该方法的实用性及其计算要求。还提供了其更广泛适用性的结论。

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