The diagnostic ability of probabilistic neural networks (PNN) for detecting sensor faults on gas turbines is examined. The structure and the features of a PNN, for sensor fault detection, are presented. It is shown that with the proposed formulation, a powerful tool for sensor fault identification is produced. A particular feature of the PNN produced is the ability to detect sensor faults even in the presence of engine component malfunction, as well as on deteriorated engines. In such situations, the size of bias that can be identified increases. The way to establish the limits of sensor bias that can be detected is presented along with results from application to test cases with realistic noise magnitudes. The diagnostic procedure proposed here is also supported by an engine performance model. The data used for setting up and testing the PNN are generated by such a model.
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July 2003
Technical Papers
Setting Up of a Probabilistic Neural Network for Sensor Fault Detection Including Operation With Component Faults
C. Romesis, Research Assistant,
C. Romesis, Research Assistant
Laboratory of Thermal Turbomachines, National Technical University of Athens, Athens 15710, Greece
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K. Mathioudakis, Associate Professor
K. Mathioudakis, Associate Professor
Laboratory of Thermal Turbomachines, National Technical University of Athens, Athens 15710, Greece
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C. Romesis, Research Assistant
Laboratory of Thermal Turbomachines, National Technical University of Athens, Athens 15710, Greece
K. Mathioudakis, Associate Professor
Laboratory of Thermal Turbomachines, National Technical University of Athens, Athens 15710, Greece
Contributed by the International Gas Turbine Institute (IGTI) of THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS for publication in the ASME JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Paper presented at the International Gas Turbine and Aeroengine Congress and Exhibition, Amsterdam, The Netherlands, June 3–6, 2002; Paper No. 2002-GT-30030. Manuscript received by IGTI, December 2001, final revision, March 2002. Associate Editor: E. Benvenuti.
J. Eng. Gas Turbines Power. Jul 2003, 125(3): 634-641 (8 pages)
Published Online: August 15, 2003
Article history
Received:
December 1, 2001
Revised:
March 1, 2002
Online:
August 15, 2003
Citation
Romesis, C., and Mathioudakis, K. (August 15, 2003). "Setting Up of a Probabilistic Neural Network for Sensor Fault Detection Including Operation With Component Faults ." ASME. J. Eng. Gas Turbines Power. July 2003; 125(3): 634–641. https://doi.org/10.1115/1.1582493
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