DocumentCode
2516646
Title
Classification of PD patterns from multiple defects
Author
Lee, June-Ho ; Okamoto, Tatsuki ; Yi, Chin Woo
Author_Institution
Dept. of Electr. Eng., Hoseo Univ., Asan, South Korea
Volume
1
fYear
2000
fDate
2000
Firstpage
463
Abstract
In this work, two approaches were proposed for the recognition of partial discharge patterns. The first approach was neural network with back-propagation algorithm, and the second approach was angle calculation between two operator vectors. PD signals were detected using three electrode systems; IEC(b), needle-plane and CIGRE method II electrode system. Both of neural network and angle comparison method showed good recognition performance for the patterns similar to the trained patterns
Keywords
backpropagation; neural nets; partial discharge measurement; pattern classification; angle comparison; backpropagation algorithm; electrical apparatus; electrode system; insulation diagnosis; multiple defects; neural network; operator vector; partial discharge; pattern classification; Dielectrics and electrical insulation; Electrodes; Neural networks; Pattern recognition; Positron emission tomography; Pulse measurements; Signal analysis; Signal detection; Testing; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Properties and Applications of Dielectric Materials, 2000. Proceedings of the 6th International Conference on
Conference_Location
Xi´an
Print_ISBN
0-7803-5459-1
Type
conf
DOI
10.1109/ICPADM.2000.875730
Filename
875730
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