Cart (Loading....) | Create Account
Close category search window
 

Partial discharge recognition through an analysis of SF6 decomposition products part 2: feature extraction and decision tree-based pattern recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Ju Tang ; State Key Lab. of Power Transm. Equip. & Syst. Security, Chongqing Univ., Chongqing, China ; Fan Liu ; Qinghong Meng ; Xiaoxing Zhang
more authors

The decomposition characteristics of the SF6 under the different kinds of partial discharges (PD) should be understood first when recognizing PD by analyzing SF6 decomposition products in gas insulated switchgear (GIS). Moreover, the characteristic quantities used for recognition must be found. In this paper, the concentration and concentration ratio of SF6 decomposition products were each selected as characteristic quantities. Fuzzy c-means clustering algorithm was adopted to assess the performance of the two types of characteristic quantities, which was based on the data of SF6 decomposition products under the four kinds of PD in Part 1. Concentration ratio had better performance than concentration as a characteristic quantity in PD recognition. The concentration ratio method for PD recognition was established based on the decision tree theory, in which the three concentration ratios, namely c(SOF2)/c(SO2F2), c(CF4)/c(CO2), and c(SOF2 +SO2F2)/c(CO2+CF4), were used as characteristic quantities. The physical significance of the three concentration ratios was also analyzed. Finally, the concentration ratio method was applied to test the performance of PD recognition. The method has a good performance and can successfully recognize different kinds of PD.

Published in:

Dielectrics and Electrical Insulation, IEEE Transactions on  (Volume:19 ,  Issue: 1 )

Date of Publication:

February 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.