DocumentCode :
1819608
Title :
PD pattern recognition of power capacitors model based on Combinational neural network
Author :
Gao, Shengyou ; Li, Fuqi ; Yu, Canghi ; Tan, Kexiong
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Volume :
1
fYear :
2003
fDate :
1-5 June 2003
Firstpage :
319
Abstract :
Five types of partial discharge (PD) models are designed to represent typical PD phenomena in power capacitors. A computer-based acoustic emission signal detecting instrument that is developed for PD is used to collect a lot of acoustic signals of model discharge. The acoustic signal duration of gas cavity discharge is very short, therefore, it is easy to be differentiated from other discharge patterns. According to the time domain and frequency domain graph of acoustic signals, the characters of oil gap discharge is close to that of discharge along oil impregnated paper surface. However, the character of discharge of metallic impurity in oil impregnated paper insulation is close to that of surface discharge of bushing. Combinational neural network (CNN) is used to recognize the five kinds of representative discharge patterns. The result shows that CNN is effective and the characteristics of acoustic signals could be used to recognize PD patterns in power capacitors.
Keywords :
acoustic emission; analogue-digital conversion; bushings; feature extraction; frequency-domain analysis; impregnated insulation; insulating oils; neural nets; partial discharges; power capacitors; preamplifiers; program processors; surface discharges; time-domain analysis; PD pattern recognition; acoustic signal duration; bushing; combinational neural network; computer-based acoustic emission signal detecting instrument; frequency domain graph; gas cavity discharge; metallic impurity; oil gap discharge; oil impregnated paper surface; power capacitors model; surface discharge; time domain analysis; Acoustic emission; Acoustic signal detection; Cellular neural networks; Neural networks; Partial discharges; Pattern recognition; Petroleum; Power capacitors; Signal detection; Surface discharges;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Properties and Applications of Dielectric Materials, 2003. Proceedings of the 7th International Conference on
ISSN :
1081-7735
Print_ISBN :
0-7803-7725-7
Type :
conf
DOI :
10.1109/ICPADM.2003.1218416
Filename :
1218416
Link To Document :
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