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Adaptive alarm processor for fault diagnosis on power transmission networks

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2 Author(s)
L. Kiernan ; Dept. of Cybern., Reading Univ., UK ; K. Warwick

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.<>

Published in:

Intelligent Systems Engineering  (Volume:2 ,  Issue: 1 )