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An Approach for Detecting Fault Lines in a Small Current Grounding System using Fuzzy Reasoning Spiking Neural P Systems

机译:基于模糊推理尖刺神经P系统的小电流接地系统故障线检测方法

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摘要

This paper presents a novel approach for detecting fault lines in a small current grounding system using fuzzy reasoning spiking neural P systems. In this approach, six features of current/voltage signals in a small current grounding system are analyzed by considering transient and steady components, respectively; a fault measure is used to quantify the possibility that a line is faulty; information gain degree is discussed to weight the importance of each of the six features; rough set theory is applied to reduce the features; and finally a fuzzy reasoning spiking neural P system is used to construct fault line detection models. Six cases in a small current grounding system prove the effectiveness of the introduced approach.
机译:本文提出了一种使用模糊推理尖峰神经P系统的小电流接地系统中故障线检测的新方法。在这种方法中,分别通过考虑瞬态和稳态分量来分析小电流接地系统中电流/电压信号的六个特征;故障度量用于量化线路故障的可能性;讨论了信息获取程度,以权衡这六个功能中每个功能的重要性;应用粗糙集理论来减少特征;最后利用模糊推理加标神经网络P系统构造故障线检测模型。小型接地系统中的六个案例证明了该方法的有效性。

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