Aircraft turbofan engine health estimation using constrained Kalman filtering

American Society of Mechanical Engineers, International Gas Turbine Institute, Turbo Expo (Publication) IGTI

Volumn 1, Issue , 2003, Pages 485-492

  Simon, Dan ^a   Simon, Donald L ^b  

^a Cleveland State University   (United States)

^b NASA GLENN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENGINE HEALTH EVALUATION; GROUND-BASED COMPUTERS;

AIRCRAFT ENGINES; COMPUTATIONAL METHODS; COMPUTER SIMULATION; ERROR ANALYSIS; HEURISTIC METHODS; KALMAN FILTERING; MONTE CARLO METHODS; PARAMETER ESTIMATION; PROBLEM SOLVING; QUADRATIC PROGRAMMING;

TURBOFAN ENGINES;

EID: 0348207994     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/GT2003-38584     Document Type: Conference Paper

References (20)

1. D. Massicotte, R. Morawski, and A. Barwicz, Incorporation of a positivity constraint into a Kalman-filter-based algorithm for correction of spectrometric data, IEEE Transactions on Instrumentation and Measurement 44(1) pp. 2-7, February 1995.
2. D. Simon and T. Chia, Kalman filtering with state equality constraints, IEEE Transactions on Aerospace and Electronic Systems, 39(1) pp. 128-136, January 2002.
3. D. Doel, TEMPER - A gas-path analysis tool for commercial jet engines, ASME Journal of Engineering for Gas Turbines and Power (116) pp. 82-89, Jan. 1994.
4. D. Doel, An assessment of weighted-least-squares-based gas path analysis, ASME Journal of Engineering for Gas Turbines and Power (116) pp. 366-373, April 1994.
5. H. DePold and F. Gass, The application of expert systems and neural networks to gas turbine prognostics and diagnostics, ASME Journal of Engineering for Gas Turbines and Power (121) pp. 607-612, Oct. 1999.
6. A. Volponi, H. DePold, R. Ganguli, and D. Chen, The use of Kalman filter and neural network methodologies in gas turbine performance diagnostics: a comparative study, Proceedings of ASME TurboExpo 2000, pp. 1-9, May 2000.
7. T. Kobayashi and D.L. Simon, A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics, 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, July 2001.
8. C. Daniele, S. Krosel, J. Szuch, and E. Westerkamp, Digital computer program for generating dynamic turbofan engine models (DIGTEM), NASA Technical Memorandum 83446, September 1983.
9. J. Szuch, S. Krosel, and W. Bruton, Automated procedure for developing hybrid computer simulations of turbofan engines, NASA Technical Paper 1851, August 1982.
10. B. Friedland, Treatment of bias in recursive filtering, IEEE Transactions on Automatic Control AC14(4) pp. 359-367, Aug. 1969.
11. H. Lambert, A simulation study of tubofan engine deterioration estimation using Kalman filtering techniques, NASA Technical Memorandum 104233, June 1991.
12. M. Roemer and G. Kacprzynski, Advanced diagnostics and prognostics for turbine engine risk assessment, IEEE Aerospace Conference, pp. 345-353, March 2000.
13. B. Anderson and J. Moore, Optimal Filtering (Prentice Hall, Englewood Cliffs, New Jersey, 1979).
14. R. Fletcher, Practical Methods of Optimization - Volume 2: Constrained Optimization (John Wiley & Sons, New York, 1981).
15. P. Gill, W. Murray, and M. Wright, Practical Optimization (Academic Press, New York, 1981).
16. C. Daniele and P. McLaughlin, The real-time performance of a parallel, nonlinear simulation technique applied to a turbofan engine, in Modeling and Simulation on Microcomputers: 1984 (R. Swartz, Ed.) Society for Computer Simulation, pp. 167-171, 1984.
17. W. Merrill, Identification of multivariable high-performance turbofan engine dynamics from closed-loop data, AIAA Journal of Guidance, Control, and Dynamics (7)6 pp. 677-683, Nov. 1984.
18. C. Chen, Linear System Theory and Design (Oxford University Press, New York, 1999).
19. O. Sasahara, JT9D engine/module performance deterioration results from back to back testing, International Symposium on Air Breathing Engines, pp. 528-535, 1985.
20. A. Gelb, Applied Optimal Estimation (MIT Press, Cambridge, Massachusetts, 1974).