Title :
Robust features selection scheme for fault diagnosis in an electric power distribution system
Author :
Butler, Karen L. ; Momoh, James A.
Author_Institution :
Dept. of Electr. Eng., Howard Univ., Washington, DC, USA
Abstract :
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
Keywords :
arcs (electric); backpropagation; distribution networks; fault location; neural nets; pattern recognition; arcing line fault detector; back-propagation; feature extraction; kurtosis; neural network input; pattern classifier; power distribution systems; reflection coefficients; robust features selection scheme; skewness; statistically derived features set; Artificial neural networks; Electrical fault detection; Fault detection; Fault diagnosis; Neural networks; Phase detection; Phase frequency detector; Power distribution; Robustness; Solids;
Conference_Titel :
Electrical and Computer Engineering, 1993. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1993.332293
