DocumentCode :
2054586
Title :
Feature extraction and pattern recognition of multi-source PD signals
Author :
Gao, Kai ; Tan, Kexiong ; Li, Fuqi ; Gao, Wensheng
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
fYear :
2001
fDate :
2001
Firstpage :
119
Lastpage :
122
Abstract :
Partial discharge signals from industrial models of stator winding bars were used to compose multisource PD patterns, which were represented by 3-D charts. The tabulated data were calculated and served as characteristic features. Pattern recognition was performed using a back-propagation (BP) network. Successful classification of multi-source PD signals showed that tabulated data were sensitive and stable to reflect different PD patterns. The suitability and robustness of the BP network for classification was further verified by analyzing the untrained patterns´ recognition
Keywords :
backpropagation; electric machine analysis computing; feature extraction; insulation testing; machine insulation; partial discharge measurement; pattern classification; stators; 3-D charts; HV power apparatus insulation systems; back-propagation network; feature extraction; industrial models; multi-source PD signals; pattern classification; pattern recognition; stator winding bars; untrained pattern recognition; Bars; Fault location; Feature extraction; Partial discharges; Pattern analysis; Pattern recognition; Power measurement; Robustness; Signal processing; Stator windings;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Insulating Materials, 2001. (ISEIM 2001). Proceedings of 2001 International Symposium on
Conference_Location :
Himeji
Print_ISBN :
4-88686-053-2
Type :
conf
DOI :
10.1109/ISEIM.2001.973580
Filename :
973580
Link To Document :
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