Vibration fault diagnosis of large generator sets using extension neural network-type 1

Authors:
Meng-hui Wang
Affiliations:
Department of Electrical Engineering, National Chin-Yi Institute of Technology, Taiping, Taichung, Taiwan, ROC
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

This paper proposes a novel neural network called Extension Neural Network-Type 1 (ENN1) for vibration fault recognition according to generator vibration characteristic spectra. The proposed ENN1 has a very simple structure and permits fast adaptive processes for new training data. Moreover, the learning speed of the proposed ENN1 is shown to be faster than the previous approaches. The proposed method has been tested on practical diagnostic records in China with rather encouraging results.