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
fDate :
12/1/1993 12:00:00 AM
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;
Journal_Title :
Electrical Insulation, IEEE Transactions on