Wind turbines states classification by a fuzzy-ART neural network with a stereographic projection as a signal normalization

Authors:
Tomasz Barszcz;Marzena Bielecka;Andrzej Bielecki;Mateusz Wójcik
Affiliations:
Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Kraków, Poland;Faculty of Gelogy, Geophysics and Environmental Protection, AGH University of Science and Technology, Kraków, Poland;Institute of Computer Science, Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland;Department of Computer Design and Graphics, Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Kraków, Poland
Venue:
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Year:
2011

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Abstract

In this paper wind turbines operational states classification is considered. The fuzzy-ART neural network is proposed as a classifying system. Applying of stereographic projection as an input signals normalization procedure is introduced. Both theoretical justification is discussed and results of experiments are presented. It turns out that the introduced normalization procedure improves classification results.