Development of a diagnostics model for the GEnx-1B turbofan engine using on-wing performance data

Master thesis (2021)

Authors

M. Otten Aerospace Engineering

Contributors

W.P.J. Visser Flight Performance and Propulsion - Aerospace Engineering (supervisor 1)
Faculty
Aerospace Engineering
Copyright: © 2021 Michiel Otten
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Published Date

10-12-2021

Language

English

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Faculty

Aerospace Engineering

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.