The paper presents the application of artificial neural network for simulation and diagnostic purposes applied to a gas turbine powered marine propulsion plant. A simulation code for the propulsion system, developed by the authors, has been extended to take into account components degradation or malfunctioning with the addition of performance reduction coefficients. The above coefficients become input variables to the analysis method and define the system status at a given operating point. The simulator is used to generate databases needed to perform a variable selection analysis and to tune response surfaces for both direct (simulation) and inverse (diagnostic) purposes. The application of the methodology to the propulsion system of an existing frigate version demonstrate the potential of the approach.
|Titolo:||Metamodels of a Gas Turbine Powered Marine Propulsion System for Simulation and Diagnostic Purposes|
|Data di pubblicazione:||2015|
|Appare nelle tipologie:||01.01 - Articolo su rivista|
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