High Impedance Fault Classification Using Wavelet Transform and Artificial Neural Network

@article{Kannan2012HighIF,
  title={High Impedance Fault Classification Using Wavelet Transform and Artificial Neural Network},
  author={Arputharaj Kannan and A. Rathinam},
  journal={2012 Fourth International Conference on Computational Intelligence and Communication Networks},
  year={2012},
  pages={831-837}
}
This paper presents a new technique based on the combination of wavelet transform(WT) and Artificial neural networks (ANNs) for addressing the problem of high impedance faults (HIFs) detection. In this paper detection of fault type has been implemented using wavelet analysis together with wavelet entropy principle and artificial neural networks. Different types of faults were studied obtaining various current waveforms. These current waveforms were decomposed using wavelet analysis into… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-3 of 3 references

Elkalash ‘‘approaches in high impedance fault detection :a chronological review’’ advances in electrical and computer engineering volume

  • M. Sedighizadeh, A. Rezazadeh, I nagy
  • 2010

Study of a new method for power system transients classification based on wavelet entropy and neural network ”

  • Zhengyou He, Shibin Gao, Xiaoqin Chen, Jun Zhang, Zhiqian Bo, Qingquan Qian

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