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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Rotor Imbalance Detection in Gas Turbines Using Fuzzy Sets
verfasst von : Ilaria Bertini, Alessandro Pannicelli, Stefano Pizzuti, Paolo Levorato, Riccardo Garbin
Erschienen in: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Verlag: Springer Berlin Heidelberg
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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.