Forecasting the health of gas turbine components through an integrated performance-based approach
Author | Tsoutsanis, E. |
Author | Meskin, Nader |
Available date | 2022-04-14T08:45:41Z |
Publication Date | 2016 |
Publication Name | 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1109/ICPHM.2016.7542829 |
Abstract | In 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. |
Sponsor | Qatar National Research Fund |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Compressibility 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 |
Type | Conference |
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Electrical Engineering [2754 items ]