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Wiring networks diagnosis using time‐domain reflectometry and support vector machines.

Authors :
Kamel Smail, Mostafa
Boubezoul, Abderrahmane
Bouchekara, Houssem R.E.H.
Sellami, Yamine
Source :
IET Science, Measurement & Technology (Wiley-Blackwell). Mar2020, Vol. 14 Issue 2, p220-224. 5p.
Publication Year :
2020

Abstract

An efficient diagnosis method dedicated to embedded wiring network based on reflectometry technique is developed in this study. The proposed methodology is based on the two complementary steps. In the first step, the time‐domain reflectometry (TDR) method is simulated, by RLCG (R: resistance, L: inductance, C: capacitance and G: conductance) circuit model and the numerical finite‐difference time‐domain method, and at the same time the datasets are created. In the second step, the support vector machine (SVM) algorithm is combined with a principal component analysis to identify the faults on wiring network from the TDR response. Two types of SVM models have been used in the diagnosis procedure: SVM classifiers and SVM regression models. In order to illustrate the performances and the feasibility of the proposed approach, numerical and experimental results are presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17518822
Volume :
14
Issue :
2
Database :
Academic Search Index
Journal :
IET Science, Measurement & Technology (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
147993461
Full Text :
https://doi.org/10.1049/iet-smt.2019.0122