Application of wavelet theory to power distribution systems for fault detection

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Description

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.

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7 p.

Creation Information

Momoh, J. & Rizy, D. T. March 1996.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

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  • Momoh, J. Howard Univ., Washington, DC (United States). Dept. of Electrical Engineering
  • Rizy, D. T. Oak Ridge National Lab., TN (United States)

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Description

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.

Physical Description

7 p.

Notes

OSTI as DE96006713

Source

  • Biennial international conference on intelligent systems applications, Orlando, FL (United States), 28 Jan - 2 Feb 1996

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  • Other: DE96006713
  • Report No.: CONF-960115--1
  • Grant Number: AC05-84OR21400
  • Office of Scientific & Technical Information Report Number: 206648
  • Archival Resource Key: ark:/67531/metadc667061

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Creation Date

  • March 1996

Added to The UNT Digital Library

  • June 29, 2015, 9:42 p.m.

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  • Jan. 25, 2016, 12:11 p.m.

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Momoh, J. & Rizy, D. T. Application of wavelet theory to power distribution systems for fault detection, article, March 1996; Tennessee. (digital.library.unt.edu/ark:/67531/metadc667061/: accessed August 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.