LOCALIZATION OF WINDING SHORTS USING FUZZIFIED NEURAL NETWORKS

Citation
Ma. Elsharkawi et al., LOCALIZATION OF WINDING SHORTS USING FUZZIFIED NEURAL NETWORKS, IEEE transactions on energy conversion, 10(1), 1995, pp. 140-146
Citations number
17
Categorie Soggetti
Engineering, Eletrical & Electronic","Energy & Fuels
ISSN journal
08858969
Volume
10
Issue
1
Year of publication
1995
Pages
140 - 146
Database
ISI
SICI code
0885-8969(1995)10:1<140:LOWSUF>2.0.ZU;2-C
Abstract
Shorted turns in field winding of large turbogenerators are difficult to detect and localize. We propose a technique whereby shorts are dete cted and localized using an artificial neural network with a fuzzified output. The method is based on injecting two simultaneous and identic al waveform signals at both ends of the field winding. Selected featur es of the received signals are used to train the neural network. Once trained, the neural network can detect and localize short turns in the field winding. The proposed method is verified by a field test on 60 MVA turbogenerator. The results show that the proposed method is quite accurate and efficient.