期刊名称：International Journal of Computer, Information, and Systems Science, and Engineering
印刷版ISSN：1307-2331
出版年度：2007
卷号：1
期号：3
出版社：World Academy of Science, Engineering and Technology
摘要：This paper presents a new method to detect high
impedance faults in radial distribution systems. Magnitudes of third
and fifth harmonic components of voltages and currents are used as a
feature vector for fault discrimination. The proposed methodology
uses a learning vector quantization (LVQ) neural network as a
classifier for identifying high impedance arc-type faults. The network
learns from the data obtained from simulation of a simple radial
system under different fault and system conditions. Compared to a
feed-forward neural network, a properly tuned LVQ network gives
quicker response.
关键词：Fault identification, distribution networks, high
impedance arc-faults, feature vector, LVQ networks.
Loading...
