Title :
Fault detection in large AC machines
Author :
Foda, S.G. ; Abdel-Rahman, M.H. ; Addoweesh, K.E.
Author_Institution :
Dept. of Electr. Eng., King Saud Univ., Riyadh, Saudi Arabia
Abstract :
The emerging techniques of artificial neural networks (ANNs) are applied to the problem of developing an artificial neural system capable of detecting interlayer faults in large AC machines using line-end coil voltage measurements. The proposed ANN system is a two-layer back propagation neural network, which is basically a classifier capable of recognizing data vectors buried in noise. The developed ANN system is fast to train and produced reliable fault detection and localization with noisy measurements. Furthermore, the proposed system needs neither data pre-processing nor feature extraction networks.
Keywords :
AC machines; backpropagation; coils; fault location; machine testing; neural nets; ANN system; artificial neural networks; classifier; data vectors; fault detection; fault localization; interlayer faults; large AC machines; line-end coil voltage measurements; noisy measurements; two-layer back propagation network; AC machines; Artificial neural networks; Coils; Electrical fault detection; Fault detection; Fault diagnosis; Neural networks; Nose; Surges; Voltage;
Conference_Titel :
Microelectronics, 2001. ICM 2001 Proceedings. The 13th International Conference on
Print_ISBN :
0-7803-7522-X
DOI :
10.1109/ICM.2001.997520