Adaptive alarm processor for fault diagnosis on power transmission networks
作者:
L.Kiernan,
K.Warwick,
期刊:
Intelligent Systems Engineering
(IET Available online 1993)
卷期:
Volume 2,
issue 1
页码: 25-37
年代: 1993
DOI:10.1049/ise.1993.0004
出版商: IEE
数据来源: IET
摘要:
In this paper we describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive on-line 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.
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