NDLI: Optimization of partial discharge detection in high voltage cables based on advanced signal processing techniques

Content Provider	IEEE Xplore Digital Library
Author	Candel, I. Digulescu, A. Ioana, C. Serbanescu, A. Sofron, E.
Copyright Year	2012
Description	Author affiliation: Polytechnic National Institute Grenoble, GIPSA-Lab, France (Candel, I.; Ioana, C.) \|\| University of Piteşti, Faculty of Electronics Communications and Computers, Romania (Sofron, E.) \|\| Military Technical Academy, Faculty of Electronics and Computer Science for Military Systems, Bucharest, Romania (Digulescu, A.; Serbanescu, A.)
Abstract	In this paper we approach the challenges of partial discharges (PD) detection in high voltage cables using signal processing techniques based on time frequency methods combined with Recurrence Plot Analysis (RPA) and high order spectrum analysis (HOSA). Detection of PD poses many problems in terms of speed of calculation, selection criteria and multitude of causes which lead to the occurrence of PD. In order to overcome these drawbacks, we have developed an algorithm which uses the spectrogram to perform a fast detection of parts from the signal which are susceptible of PD activity. The second stage calculates for each zone a detection curve using the HOSA concept of bispectrum and RPA. The latter has been applied in many non-linear systems in order to characterize the process on the basis of the recurrence matrix obtained from a time series given by the system.
Starting Page	1278
Ending Page	1282
File Size	1017280
Page Count	5
File Format	PDF
ISBN	9781467303811
e-ISBN	9781467303828
e-ISBN	9781467303804
DOI	10.1109/ISSPA.2012.6310489
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-02
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Abstracts Noise detection curve signal processing partial discharge time frequency methods RPA HOSA
Content Type	Text
Resource Type	Article

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