DocumentCode
3264760
Title
Fuzzy ART neural network approach for incipient fault detection and isolation in rotating machines
Author
Roehl, N.M. ; Pedreira, C.E. ; De Azevedo, H. R Teles
Author_Institution
CEPEL, Electr. Power Res. Center, Rio de Janeiro, Brazil
Volume
1
fYear
1995
fDate
Nov/Dec 1995
Firstpage
538
Abstract
A neural network approach for online detection and isolation of faults in rotating machines is proposed. The methodology is based on clustering of shaft vibration monitoring data by using fuzzy ART neural networks. Fault isolation is obtained by retrieving stored associations among known physical faults and clusters. The proposed scheme is implemented to detect and isolate different operation modes in an hydro generator
Keywords
ART neural nets; electric machines; fault diagnosis; fault location; fuzzy neural nets; hydroelectric generators; monitoring; pattern recognition; fault isolation; fuzzy ART neural network; hydrogenerator; incipient fault detection; operation modes; rotating machines; shaft vibration monitoring data clustering; Artificial neural networks; Clustering algorithms; Electrical fault detection; Fault detection; Fuzzy neural networks; Intelligent networks; Monitoring; Neural networks; Rotating machines; Shafts; Subspace constraints; Vibrations;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488235
Filename
488235
Link To Document