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

Abstract

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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Published
2018-07-25
How to Cite
RONG, Haina et al. An Approach for Detecting Fault Lines in a Small Current Grounding System using Fuzzy Reasoning Spiking Neural P Systems. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 13, n. 4, p. 521-536, july 2018. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/3220>. Date accessed: 26 sep. 2020. doi: https://doi.org/10.15837/ijccc.2018.4.3220.

Keywords

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