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


  • Haina Rong
  • Mianjun Ge
  • Gexiang Zhang Southwest Jiaotong University
  • Ming Zhu


Membrane computing, P system, spiking neural P systems, fault line detection, feature analysis, information gain degree, rough set theory


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.

Author Biography

Gexiang Zhang, Southwest Jiaotong University

School of Electrical Engineering


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