Detection and Location of Defects in Wiring Networks Using Time-Domain Reflectometry and Neural Networks

Author

Smail, M.K. ; Hacib, T. ; Pichon, L. ; Loete, F.

Author_Institution

Lab. de Genie Electr. de Paris, Univ. Paris-Sud, Gif-sur-Yvette, France

Volume

47

Issue

5

fYear

2011

fDate

5/1/2011 12:00:00 AM

Firstpage

1502

Lastpage

1505

Abstract

This paper presents a new technique to reconstruct faulty wiring networks and/or to localize the defects affecting the branches of the wiring network from the time domain reflectometry response. The method is also for characterization of defects in branches on the network. The direct model for wave propagation along the transmission lines is modeled by RLCG circuit parameters computed by finite elements method (FEM) or analytical solution and the finite difference time-domain (FDTD) method. Neural networks (NNs) are used to solve the inverse problem. A set of experimental results is carried out in order to validate the calculations.

Keywords

finite difference time-domain analysis; finite element analysis; neural nets; power engineering computing; power transmission faults; power transmission lines; time-domain reflectometry; wave propagation; RLCG circuit parameters; defect detection; defect location; finite difference time-domain method; finite elements method; neural networks; time-domain reflectometry; transmission lines; wave propagation; wiring networks; Artificial neural networks; Circuit faults; Impedance; Time domain analysis; Training; Wires; Wiring; Finite difference time-domain (FDTD) method; multiconductor transmission lines (MTL); network fault diagnosis; neural networks; time-domain reflectometry (TDR);

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/TMAG.2010.2089503

Filename

5754769