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Application of wavelet theory to power distribution systems for fault detection [electronic resource].

Published:
Washington, D.C. : United States. Dept. of Energy, 1996.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description:
7 pages : digital, PDF file
Additional Creators:
Oak Ridge National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary:
In this paper an investigation of the wavelet transform as a means of creating a feature extractor for Artificial Neural Network (ANN) training is presented. The study includes a teresstrial-based 3 phase delta power distribution system. Faults were injected into the system and data was obtained from experimentation. Graphical representations of the feature extractors obtained in the time domain, the frequency domain and the wavelet domain are presented to ascertain the superiority of the wavelet ``reform feature extractor.
Report Numbers:
E 1.99:conf-960115--1
conf-960115--1
Subject(s):
Other Subject(s):
Note:
Published through SciTech Connect.
03/01/1996.
"conf-960115--1"
"DE96006713"
Biennial international conference on intelligent systems applications, Orlando, FL (United States), 28 Jan - 2 Feb 1996.
Momoh, J.; Rizy, D.T.
Funding Information:
AC05-84OR21400
View MARC record | catkey: 14757927