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The Recognition Study of Impulse and Oscillation Transient Based on Spectral Kurtosis and Neural Network

  • Qiaoge Zhang
  • Zhigang Liu
  • Gang Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)

Abstract

To improve the precision of classification and recognition of transient power quality disturbances, a new algorithm based on spectral kurtosis (SK) and neural network is proposed. In the proposed algorithm, Morlet complex wavelet is used to obtain the WT-based SK of two kinds of disturbances, such as the impulse transient and oscillation transient. Two characteristic quantities, i.e., the maximum value of SK and the frequencies of the signals, are chosen as the input of neural network for the classification and recognition of transient power quality disturbances. Simulation results show that the transient disturbance characteristics can be effectively extracted by WT-based SK. With RBF neural network, the two kinds of transient disturbances can be effectively classified and recognized with the method in the paper.

Keywords

Impulse and Oscillation Transient Classification and Recognition Spectral Kurtosis Neural Network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Qiaoge Zhang
    • 1
  • Zhigang Liu
    • 1
  • Gang Chen
    • 1
  1. 1.School of Electrical EngineeringSouthwest Jiaotong UniversityChengduChina

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