Hardware Development for the Controlled Fault Injection into a Turbofan Engine Air-Bleed Valve



George E. Gorospe Donald L. Simon Kai F. Goebel


Gas path fault diagnostics assists operators in determining, and managing the health of gas turbine engines. Engine data depicting fault progression under realistic operating conditions is useful for the maturation of these diagnostic methods. In this paper, we present hardware created to inject a progressive fault in an air bleed valve of a high bypass turbofan engine during on-wing engine testing. The developed hardware interrupts and overrides the engine control computer’s command of the valve and allows for the nondestructive, progressive off-schedule operation of the air bleed valve. Numeri- cal simulation results based on NASA’s Commercial Modular Aero-Propulsion System Simulation 40k are presented to illustrate representative changes in measured engine parameters that can be expected during such an experiment.

How to Cite

E. Gorospe, G. ., L. Simon, D. ., & F. Goebel, K. . (2015). Hardware Development for the Controlled Fault Injection into a Turbofan Engine Air-Bleed Valve. Annual Conference of the PHM Society, 7(1). https://doi.org/10.36001/phmconf.2015.v7i1.2546
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Turbofan engine, Fault injection

Boyle, D. K. (2014). Preliminary study on acoustic detection of faults experienced by a high-bypass turbofan engine.

Hunter, G. W., Lekki, J., & Simon, D. (2014). Overview of vehicle integrated propulsion research (vipr) testing. In Meeting abstracts (pp. 464–464).

Li, Y. (2002). Performance-analysis-based gas turbine diagnostics: A review. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 216(5), 363–377.

Linke-Diesinger, A. (2008). Systems of commercial turbofan engines: An introduction to systems functions. Springer.

May, R. D., Csank, J., Lavelle, T. M., Litt, J. S., & Guo, T.-H. (2010). A high-fidelity simulation of a generic commercial aircraft engine and controller. National Aeronautics and Space Administration, Glenn Research Center.

Rinehart, A. W., & Simon, D. L. (2014). An integrated architecture for aircraft engine performance monitoring and fault diagnostics: Engine test results.

Volponi, A. J., DePold, H., Ganguli, R., & Daguang, C. (2003). The use of kalman filter and neural network methodologies in gas turbine performance diagnostics: a comparative study. Journal of Engineering for Gas Turbines and Power, 125(4), 917–924.
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