DocumentCode :
984945
Title :
PD pattern recognition with neural networks using the multilayer perceptron technique
Author :
Mazroua, Amira A. ; Salama, M.M.A. ; Bartnikas, R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
Volume :
28
Issue :
6
fYear :
1993
fDate :
12/1/1993 12:00:00 AM
Firstpage :
1082
Lastpage :
1089
Abstract :
The partial discharge (PD) pattern recognition capability of a neural network, employing the multilayer perceptron technique with data input based on five discharge pulse form parameters, is examined. Simple discharge sources, consisting of artificially created cylindrical cavities with metallic and dielectric electrodes, are employed. The PD pattern discrimination capability is tested using cavities of equal depth but with different electrodes, and cavities of varying depths but with similar electrodes. Preliminary test results are positive
Keywords :
charge measurement; feedforward neural nets; insulation testing; partial discharges; pattern recognition; 2D feature patterns; artificially created cylindrical cavities; backpropagation training algorithm; dielectric electrodes; discharge pulse form parameters; learning curves; metallic electrodes; multilayer perceptron; neural networks; partial discharge; pattern discrimination capability; pattern recognition; Artificial neural networks; Dielectrics; Electrodes; Fault location; Multi-layer neural network; Multilayer perceptrons; Neural networks; Partial discharges; Pattern recognition; Testing;
fLanguage :
English
Journal_Title :
Electrical Insulation, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9367
Type :
jour
DOI :
10.1109/14.249382
Filename :
249382
Link To Document :
بازگشت