Aircraft turbofan engine health estimation using constrained Kalman filtering

Journal of Engineering for Gas Turbines and Power

Volumn 127, Issue 2, 2005, Pages 323-328

  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

ALGORITHMS; COMPUTATIONAL METHODS; COMPUTER SIMULATION; HEURISTIC METHODS; KALMAN FILTERING; QUADRATIC PROGRAMMING; SERVICE LIFE;

AIRCRAFT TURBOFAN ENGINES; COMPONENT HEALTH PARAMETERS; SIGNAL INFORMATIONS; STATE-VARIABLE CONSTRAINTS;

TURBOFAN ENGINES;

JET ENGINE;

EID: 19144364093     PISSN: 07424795     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.1789153     Document Type: Article

References (20)

1. Massicotte, D., Morawski, R., and Barwicz, A., 1995, "Incorporation of a Positivity Constraint Into a Kalman-Filter-Based Algorithm for Correction of Spectrometric Data," IEEE Trans. Instrum. Meas., 44 , pp. 2-7.
2. Simon, D., and Chia, T., 2002, "Kalman Filtering With State Equality Constraints," IEEE Trans. Aerosp. Electron. Syst., 39, pp. 128-136.
3. Doel, D., 1994, "TEMPER - A Gas-Path Analysis Tool for Commercial Jet Engines," ASME J. Eng. Gas Turbines Power, 116, pp. 82-89.
4. Doel, D., 1994, "An Assessment of Weighted-Least-Squares-Based Gas Path Analysis," ASME J. Eng. Gas Turbines Power, 116, pp. 366-373.
5. DePold, H., and Gass, F., 1999, "The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics," ASME J. Eng. Gas Turbines Power, 121, pp. 607-612.
6. Volponi, A., 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 J. Eng. Gas Turbines Power, 125, pp. 917-924.
7. Kobayashi, T., and Simon, D. L., 2001, "A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics," 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, Salt Lake City, UT.
8. Daniele, C., Krosel, S., Szuch, J., and Westerkamp, E., 1983, "Digital Computer Program for Generating Dynamic Turbofan Engine Models (DIGTEM)," NASA Technical Memorandum 83446.
9. Szuch, J., Krosel, S., and Bruton, W., 1982, "Automated Procedure for Developing Hybrid Computer Simulations of Turbofan Engines," NASA Technical Paper 1851.
10. Friedland, B., 1969, "Treatment of Bias in Recursive Filtering," IEEE Trans. Autom. Control, AC14, pp. 359-367.
11. Lambert, H., 1991, "A Simulation Study of Tubofan Engine Deterioration Estimation Using Kalman Filtering Techniques," NASA Technical Memorandum 104233.
12. Roemer, M., and Kacprzynski, G., 2000, "Advanced Diagnostics and Prognostics for Turbine Engine Risk Assessment," IEEE Aerospace Conference, Big Sky, MT., pp. 345-353.
13. Anderson, B., and Moore, J., 1979, Optimal Filtering, Prentice-Hall, Englewood Cliffs, NJ.
14. Fletcher, R., 1981, Practical Methods of Optimization, Vol. 2: Constrained Optimization, Wiley, New York.
15. Gill, P., Murray, W., and Wright, M., 1981, Practical Optimization , Academic, New York.
16. Daniele, C., and McLaughlin, P., 1984, "The Real-Time Performance of a Parallel, Nonlinear Simulation Technique Applied to a Turbofan Engine," Modeling and Simulation on Microcomputers, R. Swartz, ed., Society for Computer Simulation, San Diego, CA, pp. 167-171.
17. Merrill, W., 1984, "Identification of Multivariable High-Performance Turbofan Engine Dynamics From Closed-Loop Data," J. Guid. Control Dyn., 7, pp. 677-683.
18. Chen, C., 1999, Linear System Theory and Design, Oxford University Press, New York.
19. Sasahara, O., 1985, "JT9D Engine/Module Performance Deterioration Results From Back to Back Testing," International Symposium on Air Breathing Engines, Beijing, pp. 528-535.
20. Gelb, A., 1974, Applied Optimal Estimation, MIT Press, Cambridge, MA.