Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/11210,
  title    = {High Impedance Fault Detection using LVQ Neural Networks },
  author    = {Abhishek Bansal and  G. N. Pillai},
  country   = {},
  institution={},
  abstract  = {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. },
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {1},
  number    = {4},
  year      = {2007},
  pages     = {701 - 705},
  ee        = {http://waset.org/publications/11210},
  url       = {http://waset.org/Publications?p=4},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 4, 2007},
}