Authors: Jae Eun Yoon Jong Jun Lee Tong Seop Kim Jeong L Sohn
Publish Date: 2008/12/01
Volume: 22, Issue: 12, Pages: 2516-
Abstract
Deteriorated performance data of a micro gas turbine were generated and the artificial neural network was applied to predict the deteriorated component characteristics A program to simulate operation of a micro gas turbine was set up and deterioration of each component compressor turbine and recuperator was modeled by changes in the component characteristic parameters such as compressor and turbine efficiency their flow capacities and recuperator effectiveness and pressure drop Single and double faults degradation of single and two parameters were simulated The neural network was trained with a majority of the generated deterioration data Then the remaining data were used to check the predictability of the neural network Given measurable performance parameters as inputs to the neural network characteristic parameters of each component were predicted and compared with original data The neural network produced sufficiently accurate prediction Using a smaller number of input parameters decreased prediction accuracy However an acceptable accuracy was observed even without information on several input parametersProf TS Kim received his PhD degree from Dept of Mechanical Engineering Seoul National University in 1995 He has been with Dept of Mechanical Engineering Inha Univeristy since 2000 and is Associate Professor as of Oct 2008 His research area is aerothermodynamc simulation and test of gas turbine systems including microturbine and their components His recent research concern also includes analysis on fuel cells and fuel cell/gas turbine hybrid systemsProf JL Shon received his PhD degree from Dept of Mechanical Engineering The University of Alabama in Huntsville in 1986 He has been with School of Mechanical Aerospace Engineering Seoul National University since 2000 and is BK Associate Professor as of Oct 2008 His research area is design simulation and test of gas turbine system and components He is also interested in researches on fuel cells and fuel cell/gas turbine hybrid systems
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