DocumentCode
1644078
Title
Pattern recognition of PD in large turbine generators with a neural network system
Author
Wu, Guangning ; Xie, Hengkun ; Ma, Hui ; Jiang, Xiongwei ; Chen, Zhiqing ; Sun, Delin
Author_Institution
Xi´´an Jiaotong Univ., China
Volume
1
fYear
1997
Firstpage
252
Abstract
In this paper, a neural network system used for pattern recognition of partial discharge (PD) is described. The neural network is a three-layer artificial neural system with feed forward connections, and its learning method is back propagation algorithm incorporating with an external teacher signal. Digital PD pulse signal can be obtained by a PD pulse digitized record system. Combination of the discharge magnitude, the phase angle of applied voltage at which PD occurs, and the numbers of pulse counts are taken as the input of the neural network system. After learning typical input patterns, the neural network may discriminate unknown patterns successfully. Some new results are given, and practical application of neural network for pattern recognition of PD in large turbine generators is also discussed
Keywords
backpropagation; feedforward neural nets; insulation testing; machine insulation; machine testing; partial discharges; pattern recognition; turbogenerators; backpropagation algorithm; digital PD pulse signal; external teacher; learning; partial discharge; pattern recognition; three-layer feed-forward artificial neural network; turbine generator; Dielectrics and electrical insulation; Intelligent networks; Multilayer perceptrons; Neural networks; Partial discharge measurement; Partial discharges; Pattern recognition; Power generation; Turbines; Voltage;
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.1997.617575
Filename
617575
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