DocumentCode
776318
Title
Toward automatic classification of partial discharge sources with neural networks
Author
Hirata, Akimasa ; Nakata, Syou ; Kawasaki, Zen-Ichiro
Author_Institution
Nagoya Inst. of Technol., Japan
Volume
21
Issue
1
fYear
2006
Firstpage
526
Lastpage
527
Abstract
In this letter, we propose an automatic classification scheme of discharge sources on the basis of Fourier spectrum for received electromagnetic (EM) pulses. Confirming the reproducibility of EM pulses from each source validates this scheme. The recognition rate for six discharge sources is 80% or better. The feature of our system is time efficient and to treat hundreds of pulses.
Keywords
Fourier analysis; neural nets; partial discharge measurement; power apparatus; power engineering computing; signal classification; Fourier spectrum; neural networks; partial discharge sources automatic classification; received electromagnetic pulses; Dielectrics and electrical insulation; Fault location; Multiple signal classification; Neural networks; Partial discharges; Power system reliability; Pulse power systems; Remote sensing; Reproducibility of results; Sensor arrays; Digital systems; fault diagnosis; neural-network applications; partial discharges;
fLanguage
English
Journal_Title
Power Delivery, IEEE Transactions on
Publisher
ieee
ISSN
0885-8977
Type
jour
DOI
10.1109/TPWRD.2005.848439
Filename
1564248
Link To Document