Title :
On-line diagnosis for shorted field-turns of synchronous generator based on artificial neural networks
Author :
Ding, Jianyong ; Chen, Yunpin
Author_Institution :
Wuhan Univ. of Hydraulic & Electr. Eng., China
Abstract :
A technique whereby synchro-generator shorted turns in the field winding is detected on-line using an artificial neural network (ANN) with fuzzified output. It is independent on mathematical models and parameters of the synchro-generator. The diagnostic ANN model, adaptive training algorithm and schematic circuit are proposed. Results of dynamic experiments show that the method is efficient and accurate
Keywords :
electric machine analysis computing; fault diagnosis; learning (artificial intelligence); neural nets; synchronous generators; adaptive training algorithm; artificial neural networks; diagnostic ANN model; fuzzified output; mathematical models; on-line diagnosis; schematic circuit; shorted field-turns; synchronous generator; Artificial neural networks; Circuit faults; Fault diagnosis; Harmonic analysis; Neurons; Preventive maintenance; Rotors; Stator windings; Synchronous generators; Vibration measurement;
Conference_Titel :
Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-6338-8
DOI :
10.1109/ICPST.2000.898229
