Adaptive alarm processor for fault diagnosis on power transmission networks

L. Kiernan, K. Warwick
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引用次数: 6

Abstract

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.
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输电网故障诊断的自适应报警处理器
提出了一种基于遗传算法的学习分类器系统(LCS),用于输电网故障的自适应在线诊断。该系统监视由传输网络产生的开关设备指示,报告故障诊断的任何模式指示故障组件。该系统通过国家电网公司开发的故障模拟器对故障诊断的准确性进行评估,并采用遗传算法进行适应,以反映当前的网络拓扑结构。
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