Rotor Imbalance Detection in Gas Turbines Using Fuzzy Sets

Authors:
Ilaria Bertini;Alessandro Pannicelli;Stefano Pizzuti;Paolo Levorato;Riccardo Garbin
Affiliations:
ENEA, Casaccia' R.C., Rome, Italy 00123;ENEA, Casaccia' R.C., Rome, Italy 00123;ENEA, Casaccia' R.C., Rome, Italy 00123;Ansaldo Energia S.p.A., Genoa, Italy 16152;Ansaldo Energia S.p.A., Genoa, Italy 16152
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Year:
2009

Citing 3
Cited 0

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Abstract

The paper focuses on the application of fuzzy sets in fault detection. The objective is to detect faults to an industrial gas turbine, with emphasis on the imbalance occurred in the rotor of the gas turbine. Such a fault has a certain degree of uncertainty and an index based on fuzzy sets has been developed in order to provide a fault confidence degree (0 meaning no fault, 1 the fault has been detected by all the sensors). Experimentation has been carried out on three real industrial turbines and it has shown the reliability and effectiveness of the methodology.