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Entropy 2016, 18(12), 437; doi:10.3390/e18120437

Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals

School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
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Academic Editor: Carlo Cattani
Received: 9 August 2016 / Revised: 25 November 2016 / Accepted: 2 December 2016 / Published: 7 December 2016
(This article belongs to the Special Issue Wavelets, Fractals and Information Theory II)
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Abstract

In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE) and Shannon wavelet packet entropy (SWPE) are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of transient signals and transient fault recognition. For wavelet aliasing at adjacent scale of wavelet decomposition, the impact of wavelet aliasing is analyzed for feature extraction accuracy of SWE and SWPE, and their differences are compared. Meanwhile, the analyses mentioned are verified by partial discharge (PD) feature extraction of power cable. Finally, some new ideas and further researches are proposed in the wavelet entropy mechanism, operation speed and how to overcome wavelet aliasing. View Full-Text
Keywords: Shannon wavelet entropy; Shannon wavelet packet entropy; power system; transient power signals; wavelet aliasing; accuracy of the feature extraction Shannon wavelet entropy; Shannon wavelet packet entropy; power system; transient power signals; wavelet aliasing; accuracy of the feature extraction
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, J.; Dou, Y.; Li, Y.; Li, J. Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals. Entropy 2016, 18, 437.

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