DocumentCode
2116356
Title
Partial Discharge Pattern Recognition Using Radial Basis Function Neural Network
Author
Chang, Wen-Yeau
Author_Institution
Dept. of Electr. Eng., St. John´´s Univ., Taipei, Taiwan
fYear
2010
fDate
28-31 March 2010
Firstpage
1
Lastpage
4
Abstract
This paper proposed a novel radial basis function (RBF) neural network based recognition method to identify the insulation defects of high voltage electrical apparatus arising from partial discharge (PD). Basically, a defect of insulation, as resulting from PD, would have a corresponding particular pattern. Therefore, pattern recognition of PD is significant to discriminate insulation conditions of electrical apparatus. Pattern recognition of PD aims at recognizing the defects causing the PD, such as internal discharge, external discharge, or corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of insulators by using feature vectors of field-test PD patterns. The experimental data are found to be in close agreement. The test results show that the proposed approach is efficient and reliable.
Keywords
electric machine analysis computing; insulation; partial discharges; pattern recognition; power supplies to apparatus; radial basis function networks; corona; external discharge; feature vectors; high voltage electrical apparatus; insulation defects; internal discharge; partial discharge; pattern recognition; radial basis function neural network; Circuit testing; Dielectrics and electrical insulation; Feature extraction; Insulator testing; Mathematical model; Neural networks; Partial discharges; Pattern recognition; Power transformer insulation; Radial basis function networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location
Chengdu
Print_ISBN
978-1-4244-4812-8
Electronic_ISBN
978-1-4244-4813-5
Type
conf
DOI
10.1109/APPEEC.2010.5449354
Filename
5449354
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