DocumentCode :
1646185
Title :
An overview of application of artificial neural network to partial discharge pattern classification
Author :
Cho, Kyu-Bock ; Oh, Joo-Young
Author_Institution :
Dept. of Electr. Eng., Hanseo Univ., Chungam, South Korea
Volume :
1
fYear :
1997
Firstpage :
326
Abstract :
This paper presents an overview of an artificial neural network(ANN) based partial discharge (PD) distribution pattern recognition problem to power system application. After referring briefly to the developments of ANN technique-based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical application in test laboratories and on site. The structure of a PD data base and selection of learning of PD data pattern, extraction of relevant characteristic feature or information for PD recognition are discussed. Some practical problems encountered in the neuro-fuzzy techniques based real time PD recognition are also addressed
Keywords :
fuzzy neural nets; insulation testing; partial discharges; pattern classification; PD measurement; artificial neural network; database; learning; partial discharge; pattern classification; power system; real time neuro-fuzzy technique; Artificial neural networks; Character recognition; Data mining; Laboratories; Paper technology; Partial discharge measurement; Partial discharges; Pattern recognition; Power system measurements; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Properties and Applications of Dielectric Materials, 1997., Proceedings of the 5th International Conference on
Conference_Location :
Seoul
Print_ISBN :
0-7803-2651-2
Type :
conf
DOI :
10.1109/ICPADM.1997.617594
Filename :
617594
Link To Document :
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