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A Study on fault Detection of Off-design Performance for Smart UAV Propulsion System  

Kong, Chang-Duk (조선대학교 항공우주공학과)
Kho, Seong-Hee (조선대학교 항공우주공학과)
Ki, Ja-Young ((주)이지가스터빈 R&D)
Lee, Chang-Ho (한국항공우주연구원 스마트무인기 기술개발사업단)
Publication Information
Journal of the Korean Society of Propulsion Engineers / v.11, no.3, 2007 , pp. 29-34 More about this Journal
Abstract
In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.
Keywords
SIMULINK; Neural Network; Performance Analysis; Genetic Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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