AUTOMATIC PARAMETRIC FAULT DETECTION IN COMPLEX ANALOG SYSTEMS BASED ON A METHOD OF MINIMUM NODE SELECTION

被引：8

作者：

Bilski, Adrian ^{[1
]}

Wojciechowski, Jacek ^{[1
]}

机构：

[1] Warsaw Univ Life Sci SGGW, Fac Appl Informat & Math, Ul Nowoursynowska 159, PL-02776 Warsaw, Poland

来源：

INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE | 2016年 / 26卷 / 03期

关键词：

complex analog systems; support vector machine; tabu search; genetic algorithm; parametric fault detection; SUPPORT VECTOR MACHINE; DIAGNOSIS; CIRCUITS; ALGORITHM; LOCATION;

D O I：

10.1515/amcs-2016-0045

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：655 / 668

页数：14

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