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Y. H. Liu, Y. Y. Wang and Z. H. Song, “Adaptive Fault Feature Extraction Based on Stationary Wavelet Packet Decomposition and Hilbert Transform,” Transacions of China Electrotechnical Society, Vol. 24, No. 2, 2009, pp. 145-149.

has been cited by the following article:

• TITLE: Research on the Power System Fault Classification Based on HHT and SVM Using Wide-area Information

  AUTHORS: Yiran Guo, Changqing Li, Yali Li, Shibin Gao

  KEYWORDS: Power System; Fault Classification; HHT; SVM; Cross-validation

  JOURNAL NAME: Energy and Power Engineering, Vol.5 No.4B, October 14, 2013

  ABSTRACT: A power system fault classification method based on the Hilbert-Huang transformation (HHT) and support vector machine (SVM) is proposed in this paper. According to different types of faults taking place in area and the outer area, this paper uses HHT to extract the instantaneous amplitude and Hilbert marginal spectrum of the current signal. Then a fault classifier consisting of a series of SVM classifiers that are optimized by using cross validation method is constructed. Finally, inputting the feature vector sets that are conversed by the HHT into the fault classifier, the fault type and locate the fault area will be distinguished. The simulation results show that this approach is very effective to classify the fault type especially when the sample is small.