Field studies using a neural-net-based approach for fault diagnosis in distribution networks

IEE Proceedings: Generation, Transmission and Distribution

Volumn 144, Issue 5, 1997, Pages 429-435

  Butler, K L ^a   Momoh, J A ^b   Sobajic, D J ^c  

^a TEXAS A AND M UNIVERSITY   (United States)

^b Howard University   (United States)

^c ELECTRIC POWER RESEARCH INSTITUTE   (United States)

Author keywords

Distribution systems; Neural networks; Protection

Indexed keywords

ELECTRIC FAULT LOCATION; NEURAL NETWORKS; SIGNAL PROCESSING;

FAULT DIAGNOSIS METHOD;

ELECTRIC POWER DISTRIBUTION;

EID: 0031221296     PISSN: 13502360     EISSN: None     Source Type: Journal    
DOI: 10.1049/ip-gtd:19971433     Document Type: Article

References (14)

1. WIDROW, B., and HOFF, M.E.: 'Adaptive signal processing' (Prentice-Hall, New Jersey, 1985)
2. EBRON, S., LUBKEMAN, D., and WHITE, M.: 'A neural network approach to the detection of incipient faults on power distribution feeders', IEEE Trans. Power Deliv., 1990, 5, (2), pp. 905-914
3. SULTAN, A.F., SWIFT, G.W., and FEDIRCHUK., D.J.: 'Detection of high impedance arcing faults usine a multi-layer perceptron', IEEE Trans. Power Deliv., 1992, 7, (4), pp. 1871-1877
4. SHARAF, A.M., SNIDER, L.A., and DEBNATH, K.: Third harmonic based detection of high impedance faults in distribution systems using artificial neural networks'. Proceedings of the North American Power symposium, Washington, DC, 1993, pp. 315-321
5. FERNANDO, S., and WATSON, K., : 'High impedance fault detection usina a time-delay neural network' in CIHAN, Y.C., DAGLI, H., and BURKE, L.I. (Eds.): 'Intelligent engineering through artificial neural networks, ANNIE'92'. St. Louis, Missour, (ASME Press, 1992), Vol. 2, pp. 433-438
6. CHOW, M.-Y., LEE, S.O., and TAYLOR, L.S.: 'Recognizing animal-caused faults in power distribution systems using artificial neural networks', IEEE Trans. Power Deliv., 1993, 8, (3), pp. 1268-1273
7. DALSTEIN, T., and KULICKE, B.: 'Neural network approach to fault classification for high speed protective relaying', IEEE Trans. Power Deliv., 1995, 10, (2), pp. 1002-1011
8. HAYKIN, S.: 'Neural networks - a comprehensive foundation' (Macmillan College Publishing Co., 1994)
9. MOMOH, J., DIAS, L., BUTLER, K., and LAIRD, D.: 'Selection of artificial neural networks for distribution system fault diagnosis'. Proceedings of Intelligent systems on power systems, Montpellier, France, 1994
10. Los Angeles Department of Water and Power, requests for proposals, 1989
11. BUTLER, K.L.: 'Supervised ANN based distribution fault analysis under arcing condition'. PhD dissertation, Howard University, May 1994
12. BALL, G.H., and HALL, D.J.: 'ISODATA, an iterative method of multivariable data analysis and pattern classification'. Proceedings of the IEEE international Communications conference, 1966
13. 'Detection of arcing faults on distibution feeders'. EPRI report EL-2757, prepared by Texas A&M University, December 1982
14. MORF, M., VIEIRA, A., LEE, D.T., and KAILATH, T.: 'Recursive multichannel maximum entropy spectral estimation', IEEE Trans. Geosci. Electron., 1978, GE-16, (2), pp. 85-94