Application of wavelet theory to power distribution systems for fault detection
Conference
·
OSTI ID:206648
- Howard Univ., Washington, DC (United States). Dept. of Electrical Engineering
- Oak Ridge National Lab., TN (United States)
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.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 206648
- Report Number(s):
- CONF-960115-1; ON: DE96006713
- Resource Relation:
- Conference: Biennial international conference on intelligent systems applications, Orlando, FL (United States), 28 Jan - 2 Feb 1996; Other Information: PBD: [1996]
- Country of Publication:
- United States
- Language:
- English
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