In-flight isolation of degraded engine components by shape comparison of transient outputs

Journal of Engineering for Gas Turbines and Power

Volumn 134, Issue 6, 2012, Pages

  Simmons, Jeffrey C ^a   Danai, Kourosh ^a  

^a University of Massachusetts   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPONENT DEGRADATION; CONTINUOUS WAVELET TRANSFORM; CONTINUOUS WAVELET TRANSFORMATION; DEGRADATION EFFECT; DIRECT METHOD; ENGINE COMPONENTS; ENGINE HEALTH MONITORING; ENGINE OUTPUT; ENGINE SIMULATION; HEALTH PARAMETERS; SENSORY DATA; SHAPE COMPARISON; TIME-SCALES;

AIRCRAFT ENGINES; WAVELET TRANSFORMS;

ENGINES;

EID: 84859900750     PISSN: 07424795     EISSN: 15288919     Source Type: Journal    
DOI: 10.1115/1.4005814     Document Type: Article

References (23)

1. Urban, L. A. and Volponi, A. J., 1992, Mathematical Methods of Relative Engine Performance Diagnostics., SAE Trans., J.Aerosp., 101, Technical Paper No. 922048, pp. 2025-2050.
2. Doel, D. L., 1994, TEMPER-A Gas-Path Analysis Tool for Commercial Jet Engines., ASMEJ. Eng. Gas Turbines Power, 116 (1), pp. 82-89.
3. Doel, D. L., 1994, An Assessment of Weighted-Least-Squares-Based Gas Path Analysis., ASME J. Eng. Gas Turbines Power, 116, pp. 366-373.
4. Luppold, R. H., Roman, J. R., Gallops, G. W., and Kerr, L. J., 1989, Estimating In-Flight Engine Performance Variations Using Kalman Filter Concepts., AIAA Paper No. AIAA-89-2584.
5. 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 No. 91-GT-216.
6. Mathioudakis, K., Kamboukos, Ph., and Stamatis, A., 2002, Turbofan Performance Deterioration Tracking Using Nonlinear Models and Optimization Techqniques., ASMEJ. Turbomach., 124, pp. 580-587. (Pubitemid 36065152)
7. Espana, M. D. and Gilyard, G. B., 1993, On the Estimation Algorithm used in Adaptive Performance Optimization of Turbofan Engines., NASA TM No. 4551.
8. Kobayashi, T., Simon, D. L., and Litt, J. S., 2005, Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters., Army Research Laboratory Report No.ARL-TR-2955.
9. McCusker, J. R. and Danai, K., 2010, Measurement Selection for Engine Transients by Parameter Signatures., Trans. ASME. J. Eng. Gas Turbines Power, 132 (12), p. 121601.
10. Ljung, L., 1999, System Identification: Theory for the User, 2nd ed., Prentice-Hall, Englewood Cliffs, NJ.
11. Volponi, A. J., Brotherton. T., Luppold, R., and Simon, D. L., 2004, Development of an Information Fusion System for Engine Diagnostics and Health Management., NASA/TM-2004-212924, Army Research Laboratory Report No. ARL-TR-3127.
12. 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.
13. Volponi, A. J., DePold, H., Ganguli, R., and Daguang, C., 2003, The Use of Kalman Filter and Neural Network Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study., ASMEJ. Eng. Gas Turbines Power, 125, pp. 917-924. (Pubitemid 40231411)
14. Gupta, S., Ray, A., Sarkar, S., and Yasar, M., 2008, Fault Detection and Isolation in Aircraft Gas Turbine Engines. Part 1: Underlying Concept., Proc. Inst. Mech. Eng., Part G: J.Aerosp Eng., 222, pp. 307-318.
15. Gupta, S., Ray, A., Sarkar, S., and Yasar, M., 2008, Fault Detection and Isolation in Aircraft Gas Turbine Engines. Part 2: Validation on a Simulation Test Bed., Proc. Inst. Mech. Eng., Part G:J. Aerosp. Eng., 222, pp. 319-330.
16. McCusker, J. R., Danai, K., and Kazmer, D. O., 2010, Validation of Dynamic Models in the Time-Scale Domain., ASME J. Dyn. Syst., Meas., Control, 132 (6), p. 061402.
17. Danai, K. and McCusker, J. R., 2009, Parameter Estimation by Parameter Signature Isolation in the Time-Scale Domain., ASME J. Dyn. Syst., Meas., Control, 131 (4), p. 041008.
18. McCusker, J. R., Currier, T., and Danai, K., 2011, Improved Parameter Estimation by Noise Compensation in the Time-Scale Domain., Signal Process., 91 (1), pp. 72-84.
19. Peng, Z. K. and Chu, F. L., 2004, Application of the Wavelet Transform in Machine Condition Monitoring and Fault Diagnostics: A Review With Bibliography., Mech.Syst. Signal Process., 18, pp. 199-221.
20. Mallat, S., 1998, A Wavelet Tour of Signal Processing, 2nd ed., Academic Press, San Diego.
21. Mallat, S. and Hwang, W. L., 1992, Singularity Detection and Processing with Wavelets., IEEE Trans. Inf. Theory, 38 (2), pp. 617-643.
22. Donoho, D. L. and Johnstone, I. M., 1995, Adapting to Unknown Smoothness via Wavelet Shrinkage., J. Am. Stat. Assoc., 90 (432), pp. 1200-1224. (Pubitemid 126093135)
23. Chipman, H. A., Kolaczyk, E. D., and McCulloch, R. E., 1997, Adaptive Bayesian Wavelet Shrinkage., J. Am. Stat. Assoc., 92, pp. 1413-1421.