Development of a diagnostics model for the GEnx-1B turbofan engine using on-wing performance data
Michiel Otten (TU Delft - Aerospace Engineering)
W.P.J. Visser – Mentor (TU Delft - Flight Performance and Propulsion)
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Abstract
Gas path analysis (GPA) plays a major role in turbofan condition monitoring. GPA uses thermodynamic engine models to identify deterioration of individual turbofan components. The accuracy of GPA results depends on the quality of the engine models. Turbofan performance is influenced by secondary performance parameters, which include variable geometry, active clearance control, bleeds flows and power off-take. Hence, if not accounted for in engine models, it decreases GPA accuracy.
A method is proposed to increase the accuracy of engine models by accounting for secondary performance parameters. Combining an evolutionary algorithm with on-wing engine data has resulted in a novel approach to determine relationships between secondary performance parameter settings and turbofan component performance deviation. Results show that accounting for these relationships in the engine models increases the model accuracy. Consequently, an accuracy increase of the GPA results is achieved. The method is verified with simulated data and validated with GEnx-1B on-wing engine data.