By Topic

Online source recognition of partial discharge for gas insulated substations using independent component analysis

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

6 Author(s)
Chang, C.S. ; Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore ; Jin, J. ; Chang, C. ; Hoshino, T.
more authors

To perform reliable insulation diagnosis for gas-insulated substation (GIS), detectable partial discharge (PD) should be identified quickly and effectively. With the increasing application of high voltage DC transmission, PD identification in such systems becomes more and more important. Therefore, a novel technique based on the analysis of ultra high frequency (UHF) resonance waveforms is proposed in this paper to meet the requirement. With the help of independent component analysis, the most dominating features are identified directly from UHF resonance signals without phase information. Using the identified features as the input, a neural network is implemented for recognizing sources of PD in SF6 and separating from the corona in air within a very short time

Published in:

Dielectrics and Electrical Insulation, IEEE Transactions on  (Volume:13 ,  Issue: 4 )