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Fault Line Detection in Small Current Grounding Systems Based on RBF Network

Authors: Yundong Song; Shun Yuan; Yanjie Wang; Chunfang Zhao;

Fault Line Detection in Small Current Grounding Systems Based on RBF Network

Abstract

It is a long-standing issue on fault line detection of single-phase grounding fault in the small current grounding systems. If only one fault line detection method is used, fault information will be analyzed partially, which is not enough for fault line detection; and there are different fit conditions for every method. So the single method can not ensure that the reliability of the fault line detection. In this paper, the effective domains of fault line detection through some methods were obtained by rough set theory, and the radial basis function (RBF) neural network was designed and trained, then the results of the methods based on RBF network were got. Fusing those detection results, a better fault line detection result was advanced. Simulation results by EMTP show that the fault line detection method is efficient with high value of studying and wide application future.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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