Enhanced Self Tuning On-Board Real-Time Model (Estorm) for Aircraft Engine Performance Health Tracking
Author | : National Aeronautics and Space Administration (NASA) |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 56 |
Release | : 2018-05-22 |
Genre | : |
ISBN | : 9781719488730 |
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A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation. Volponi, Al and Simon, Donald L. (Technical Monitor) Glenn Research Center TURBOFAN ENGINES; AIRCRAFT ENGINES; FAULT DETECTION; GAS TURBINE ENGINES; PERFORMANCE PREDICTION; REAL TIME OPERATION; DIAGNOSIS; DATA PROCESSING; PROPULSION