Diagnosing transmission line termination faults by means of wavelet based crosstalk signature recognition

Author

Buccella, Concettina ; Orlandi, Antonio

Author_Institution

Dept. of Electr. Eng., Aquila Univ., Italy

Volume

23

Issue

1

fYear

2000

fDate

3/1/2000 12:00:00 AM

Firstpage

165

Lastpage

170

Abstract

This paper describes a technique that allows one to identify the faulty condition (open or short circuit) at a termination of a multiconductor transmission line structure by measuring the induced voltage at the other end. The wavelet theory is used to filter out from the signal the components due to unwanted sources, and to decompose it to obtain the fault´s signature. The comparison (or matching) algorithm is substituted by an artificial neural network. Two differently designed neural networks are used to validate the results and the overall procedure is also tested on an experimental set-up

Keywords

crosstalk; fault diagnosis; multiconductor transmission lines; printed circuit testing; wavelet transforms; PCBs; artificial neural network; crosstalk signature recognition; fault signature; induced voltage; matching algorithm; multiconductor transmission line structure; open circuit; short circuit; transmission line termination faults; wavelet based methods; Artificial neural networks; Circuit faults; Distributed parameter circuits; Fault diagnosis; Filtering theory; Multiconductor transmission lines; Transmission line measurements; Transmission line theory; Transmission lines; Voltage measurement;

fLanguage

English

Journal_Title

Components and Packaging Technologies, IEEE Transactions on

Publisher

ieee

ISSN

1521-3331

Type

jour

DOI

10.1109/6144.833056

Filename

833056