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Entropy 2015, 17(11), 7698-7712;

A Novel Method for PD Feature Extraction of Power Cable with Renyi Entropy

School of Electrical Engineering, Northeast Dianli University, Jilin 132012, China
Author to whom correspondence should be addressed.
Academic Editor: Carlo Cattani
Received: 8 September 2015 / Revised: 19 October 2015 / Accepted: 10 November 2015 / Published: 13 November 2015
(This article belongs to the Special Issue Wavelets, Fractals and Information Theory)
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Partial discharge (PD) detection can effectively achieve the status maintenance of XLPE (Cross Linked Polyethylene) cable, so it is the direction of the development of equipment maintenance in power systems. At present, a main method of PD detection is the broadband electromagnetic coupling with a high-frequency current transformer (HFCT). Due to the strong electromagnetic interference (EMI) generated among the mass amount of cables in a tunnel and the impedance mismatching of HFCT and the data acquisition equipment, the features of the pulse current generated by PD are often submerged in the background noise. The conventional method for the stationary signal analysis cannot analyze the PD signal, which is transient and non-stationary. Although the algorithm of Shannon wavelet singular entropy (SWSE) can be used to analyze the PD signal at some level, its precision and anti-interference capability of PD feature extraction are still insufficient. For the above problem, a novel method named Renyi wavelet packet singular entropy (RWPSE) is proposed and applied to the PD feature extraction on power cables. Taking a three-level system as an example, we analyze the statistical properties of Renyi entropy and the intrinsic correlation with Shannon entropy under different values of α . At the same time, discrete wavelet packet transform (DWPT) is taken instead of discrete wavelet transform (DWT), and Renyi entropy is combined to construct the RWPSE algorithm. Taking the grounding current signal from the shielding layer of XLPE cable as the research object, which includes the current pulse feature of PD, the effectiveness of the novel method is tested. The theoretical analysis and experimental results show that compared to SWSE, RWPSE can not only improve the feature extraction accuracy for PD, but also can suppress EMI effectively. View Full-Text
Keywords: wavelet packet transformation; Renyi entropy; partial discharge; feature extraction wavelet packet transformation; Renyi entropy; partial discharge; feature extraction

Figure 1a

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.; Wang, Z.; Li, G. A Novel Method for PD Feature Extraction of Power Cable with Renyi Entropy. Entropy 2015, 17, 7698-7712.

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