DocumentCode
1849159
Title
Comparison of feature extraction methods in partial discharge waveform recognition
Author
Zheng, Z. ; Tan, K.
Author_Institution
Tsinghua Univ., Beijing, China
fYear
2001
fDate
2001
Firstpage
315
Lastpage
318
Abstract
Automated recognition of various types of partial discharge pulses based on the pulse waveform was investigated through application of an artificial neural network. Various feature extraction methods were applied, and the recognition efficiency was determined. The results indicate that the method based on the physical characteristics of the partial discharge, which employs expert prior knowledge, is most effective and computationally least intensive
Keywords
feature extraction; neural nets; partial discharges; waveform analysis; artificial neural network; expert prior knowledge; feature extraction methods; partial discharge waveform recognition; physical characteristics; pulse waveform; recognition efficiency; Artificial neural networks; Feature extraction; Intelligent networks; Neurons; Oil insulation; Partial discharges; Pattern recognition; Pulse measurements; Stators; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Insulation and Dielectric Phenomena, 2001 Annual Report. Conference on
Conference_Location
Kitchener, Ont.
Print_ISBN
0-7803-7053-8
Type
conf
DOI
10.1109/CEIDP.2001.963547
Filename
963547
Link To Document