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dc.creatorGabel, S.
dc.date.accessioned2010-06-23T15:10:04Z
dc.date.available2010-06-23T15:10:04Z
dc.date.issued2003-05
dc.identifier.otherESL-IE-03-05-25
dc.identifier.urihttp://hdl.handle.net/1969.1/91032
dc.description.abstractA neural network approach is employed for estimating key efficiency parameters in a gas turbine engine. The concept is demonstrated within a limited operating region for a given engine. The neural network is developed to estimate certain unmeasurable parameters in a first-principles mathematical model of the engine. The network is trained using data derived from measured data taken on an auxiliary power unit (APU) engine (from an aircraft application). A discussion of the neural network development and its application to on-line fault detection in an industrial gas turbine engine is also presented. The technique could be used for condition-based maintenance or to monitor the energy efficiency of an industrial gas turbine.en
dc.language.isoen_US
dc.publisherEnergy Systems Laboratory (http://esl.tamu.edu)
dc.subjectNeural Networksen
dc.titleUsing Neural Networksen
dc.typePresentationen


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