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AuthorTsoutsanis, E.
AuthorMeskin, Nader
Available date2022-04-14T08:45:41Z
Publication Date2016
Publication Name2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ICPHM.2016.7542829
URIhttp://hdl.handle.net/10576/29794
AbstractIn this study, we present an integrated method for detecting and forecasting the health of gas turbine components as degraded over time. An advanced model-based real time performance adaptation approach is developed for detecting the degradation of engine components via a dynamic engine model that is built in Simulink. The detected health parameters of the engine component are then implemented in a discrete window-based analysis by a regression method in order to forecast their evolution. The proposed approach is tested for an engine with increased flexibility that characterizes modern gas turbine operations. The results demonstrate the promising capabilities of our advanced proposed method for accurate and efficient detection and forecast of the health of gas turbine compressors as degraded over time. 2016 IEEE.
SponsorQatar National Research Fund
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCompressibility of gases
Engines
Forecasting
Gas compressors
Gas turbines
Health
Regression analysis
Systems engineering
Advanced modeling
Efficient detection
Engine components
Gas turbine compressors
Health parameters
Increased flexibility
Performance based approach
Real time performance
Turbine components
TitleForecasting the health of gas turbine components through an integrated performance-based approach
TypeConference Paper


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