Classification of faults and switching events by inductive reasoning and expert system methodology

IEEE Transactions on Power Delivery

Volumn 4, Issue 3, 1989, Pages 1631-1637

  Kim, C J ^a   Russell, B Don ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

expert system induction theory; high impedance fault; learning; minimum entropy; pattern classification

Indexed keywords

ARTIFICIAL INTELLIGENCE--EXPERT SYSTEMS; ELECTRIC FAULT LOCATION;

FAULT CLASSIFICATION; HIGH IMPEDANCE FAULT DETECTION; INDUCTION THEORY; MINIMUM ENTROPY METHOD; SWITCHING EVENT CLASSIFICATION;

ELECTRIC POWER SYSTEMS;

EID: 0024703311     PISSN: 08858977     EISSN: 19374208     Source Type: Journal    
DOI: 10.1109/61.32653     Document Type: Article

References (8)

1. B. G. Buchanan, E. H, Shortliffe(Ed.), Rule-Based Expert Systems, Addison-Wesley, 1985.
2. B. Don Russell, Ram P. Chinchali, C. J. Kim, “Behavior of Low Frequency Spectra during Arcing Fault and Switching Event,” IEEE PES Summer meeting, San Francisco, CA, 1987. Paper No. 87SM633-1.
3. Ronald Christensen, Entropy Minimax Sourcebook, Entropy Limited, 1980.
4. Maximum Entropy Conference:held at MIT, MIT Press, 1978.
5. B. Don Russell, K. Mehta, Ram P. Chinchali, “An Arcing Fault Detection Technique using Low Frequency Current Components-Performance Evaluation using Recorded Field Data”, IEEE PES Summer Meeting, San Francisco, CA, 1987. Paper No. 87SM634-9.
6. C. L. Benner, P. W. Carswell, B. Don Russell, “Improved Algorithm for Detecting Arcing Faults using Random Fault Behavior”, Submitted to Electric Power System Research.
7. S. L. Tanimoto, The Elements of Artificial Intelligence, Computer Science Press, 1987.
8. C. J. Kim, B. Don Russell, “Harmonic Behavior during Arcing Faults on Power Distribution Feeders”, Electric Power System Research, Vol. 14, No.3, pp. 219–225, June 1988.