Robust features selection scheme for fault diagnosis in an electric power distribution system Conference Paper

abstract

• 1993 IEEE. In this paper, the authors present a statistically derived features set for use as input to a neural network based arcing line fault detector for power distribution systems. In addition, the authors test the performance of the back-propagation artificial neural network uses values of the features set computed from laboratory experimental data. The results show great promise toward the development of an efficient artificial neural network based arcing line fault detector.

name of conference

• Proceedings of Canadian Conference on Electrical and Computer Engineering

authors

• Butler-Purry, Karen

published proceedings

• Proceedings of Canadian Conference on Electrical and Computer Engineering

author list (cited authors)

• Butler, K. L., & Momoh, J. A.

citation count

• 1

complete list of authors

• Butler, KL||Momoh, JA

publication date

• January 1993

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Canadian Conference on Electrical and Computer Engineering  Journal

Digital Object Identifier (DOI)

• 10.1109/ccece.1993.332293

International Standard Book Number (ISBN) 10

• 0780314433

start page

• 209-213 vol.1

end page

• 213

URL

• http://dx.doi.org/10.1109/ccece.1993.332293