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TECHNICAL PAPERS: Gas Turbines: Controls, Diagnostics & Instrumentation

Evaluation of an Enhanced Bank of Kalman Filters for In-Flight Aircraft Engine Sensor Fault Diagnostics

[+] Author and Article Information
Takahisa Kobayashi

QSS Group, Inc., 21000 Brookpark Road, Cleveland, OH 44135

Donald L. Simon

U.S. Army Research Laboratory, NASA Glenn Research Center, MS-77-1, 21000 Brookpark Road, Cleveland, OH 44135

J. Eng. Gas Turbines Power 127(3), 497-504 (Jun 24, 2005) (8 pages) doi:10.1115/1.1850505 History: Received October 01, 2003; Revised March 01, 2004; Online June 24, 2005
Copyright © 2005 by ASME
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References

Merrill,  W. C., DeLaat,  J. C., and Bruton,  W. M., 1988, “Advanced Detection, Isolation, and Accommodation of Sensor Failures-Real-Time Evaluation,” J. Guid. Control Dyn., 11(6), pp. 517–526.
Kobayashi, T., and Simon, D. L., 2003, “Application of a Bank of Kalman Filters for Aircraft Engine Fault Diagnostics,” ASME Paper GT2003-38550.
Volponi, A. J., 1994, “Sensor Error Compensation in Engine Performance Diagnostics,” ASME Paper 94-GT-58.
Doel,  D. L., 2003, “Interpretation of Weighted-Least-Squares Gas Path Analysis Results,” J. Eng. Gas Turbines Power, 125, pp. 624–633.
Kobayashi, T., and Simon D. L., 2001, “A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics,” Paper AIAA-2001-3763.
España, M. D., 1993, “On the Estimation Algorithm for Adaptive Performance Optimization of Turbofan Engines,” Paper AIAA-93-1823.
Volponi, A. J., DePold, H., Ganguli, R., and Chen, D., 2000, “The Use of Kalman Filter and Neural Network Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study,” ASME Paper 2000-GT-547.
Kerr, L. J., Nemec, T. S., and Gallops, G. W., 1991, “Real-Time Estimation of Gas Turbine Engine Damage Using a Control Based Kalman Filter Algorithm,” ASME Paper 91-GT-216.
Brotherton, T., Volponi, A., Luppold, R., and Simon, D. L., 2003, “eSTORM: Enhanced Self Tuning On-Board Real-Time Engine Model,” Proceedings of the 2003 IEEE Aerospace Conference, Big Sky, MT.

Figures

Grahic Jump Location
Propulsion system with sensor fault detection and isolation system
Grahic Jump Location
Architecture of the sensor FDI system
Grahic Jump Location
Architecture of piecewise Kalman filter model

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