By Topic

Classification of partial discharge sources in gas-insulated substations using novel preprocessing strategies

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 $31
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

2 Author(s)
Hamilton, D.J. ; Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK ; Pearson, J.S.

Partial discharge activity in GIS can indicate impending breakdown. The activity is recorded as characteristic point on wave records which are classified into defect types by expert engineers. Classification assists with the assessment of the risk of catastrophic failure. An automatic technique has been developed aimed at replicating the strategy used by an expert during manual classification. Preprocessing techniques have been selected which implicitly incorporate the processes used by the expert rather than applying explicit rules. Information from the records pertinent to classification is extracted using mathematical morphology techniques allowing substantial compression of the data. An artificial neural network trained with such data has been shown to produce results indicating that classification matched that of the expert

Published in:

Science, Measurement and Technology, IEE Proceedings -  (Volume:144 ,  Issue: 1 )