Title :
Novel approach to alternator field winding interturn fault detection
Author :
Auckland, D.W. ; Pickup, I.E.D. ; Shuttleworth, R. ; Wu, Y.-T. ; Zhou, C.
Author_Institution :
Dept. of Electr. Eng., Manchester Univ., UK
fDate :
3/1/1995 12:00:00 AM
Abstract :
The paper demonstrates how artificial neural networks can be used for the online detection of interturn faults on the rotor of an alternator. A simple network has been designed and tested on a laboratory micromachine. The tests have shown that by employing a neural network to predict the field current from measurements at the stator terminals, operation with a faulted rotor can be successfully identified
Keywords :
alternators; automatic test equipment; automatic testing; fault location; machine testing; neural nets; power engineering computing; rotors; stators; alternator; artificial neural networks; field current; interturn fault detection; laboratory micromachine; measurements; rotor; stator terminals; testing;
Journal_Title :
Generation, Transmission and Distribution, IEE Proceedings-
DOI :
10.1049/ip-gtd:19951712
