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N. E. Huang, Z. Shen, S. R. Long, et al, “The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis,” Proceedings of Royal Society of London, Series A, pp. 903–994, 1998.

has been cited by the following article:

• TITLE: Extracting Power Transformer Vibration Features by a Time-Scale-Frequency Analysis Method

  AUTHORS: Shuyou WU, Weiguo HUANG, Fanrang KONG, Qiang WU, Fangming ZHOU, Ruifan ZHANG, Ziyu WANG

  KEYWORDS: Power Transformer, Wavelet Packet Transform, Hilbert-Huang Transform, Mother Wavelet Selection,

  JOURNAL NAME: Journal of Electromagnetic Analysis and Applications, Vol.2 No.1, January 28, 2010

  ABSTRACT: In order to take advantage of the merits of WPT and HHT in feature extraction from vibration signals of power transformer, a time-scale-frequency analysis method is developed based on the combination of these two techniques. This method consists of two steps. First, the desirable wavelet packet nodes corresponding to characteristic frequency bands of power transformer are selected through a Correlation Degree Threshold Screening (CDTS) technique for reconstructing a time-domain signal that contains useful information of power transformer. Second, the HHT is then conducted on the reconstructed signal to track the instantaneous frequencies corresponding to natural characteristics of power transformer. Experimental results are provided by analyzing a real power transformer vibration signal. Compared with the features extracted by directly using HHT, the features obtained by the proposed method reveal clearer condition pattern of the transformer, which shows the potential of this method in condition monitoring of power transformer.