Abstract
The model-plant performance matching of aircraft engine can be used to solve several problems, such as fault diagnosis, model calibration and deterioration estimation etc. A partially mixed high bypass ration turbofan in civil aviation is modeling in simulating environments to constitute a model-plant performance matching benchmark. Depending on the nonlinear thermodynamic model between measured residuals and health factors, the regularization method with parameter competitive criterion is used to optimize the object value of components health factors. Several sets of simulated deterioration and fault data are naturalized as the invaliding cases, the better matching of model-plant is obtained from the simulating results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Doel, D.: An assessment of weighted-least-squares based gas path analysis. J. Eng. Gas Turbines Power 116(2), 366 (1994)
Doel, D.L.: Interpretation of Weighted-Least-Squares Gas Path Analysis Results. Journal of Engineering for Gas Turbines and Power 125, 625 (2003)
Mathioudakis, K., Kamboukos, P.: Assessment of Gas Path Diagnostic Schemes. ASME Turbo Expo paper GT2003-53862 (2003)
Aretakis, N., Mathioudakis, K.: Non-linear engine component fault diagnosis from a limited number of measurements using a combinatorial approach. In: Proceedings of ASME Turbo Expo 2002 ASME-GT-2002-30031 (2002)
Gulati, A., Taylor, D., Sign, R.: Multiple operating point analysis using genetic algorithm optimization for gas turbine diagnostic. In: XV ISABE, Bangalore, India, September 3-7 (2001), paper ISABE-2001-1139
Li, Y.G., Abdul Ghafir, M.F., Wang, L., et al.: Nonlinear Multiple Points Gas Turbine Off-Design Performance Adaptation Using a Genetic Algorithm. J. Eng. Gas Turbines Power 133(7), 071701(9 pages) (2011)
Li, Y.G., Marinai, L., Lo Gatto, E., Pachidis, V., Pilidis, P.: Multiple Point Adaptive Performance Simulation Tuned to Aerospace Test-Bed Data. J. Propul. Power 25(3), 635–641 (2009)
Li, Y.G.: Gas Turbine Performance and Health Status Estimation Using Adaptive Gas Path Analysis. Journal of Engineering for Gas Turbines and Power 132 (April 2010)
Roth, B.A., Doel, D.L., Cissell, J.J.: Probabilistic Matching of Turbofan Engine Performance Models to Test Data. ASME Paper No. GT2005-68201 (2005)
Henriksson, M., Léonard, O., Borguet, S., et al.: On Inverse Problems In Turbine Engine Parameter Estimation. In: ASME Turbo Expo 2007: Power for Land, Sea and Air, Montreal, Canada, May 14-17 (2007), GT2007-27756
Cerri, G., Borghetti, S., Salvini, C.: Inverse Methodologies For Actual Status Recognition Of Gas Turbine Components. In: Proceedings of PWR2005,ASME Power, Chicago, Illinois USA, April 5-7 (2005), PWR2005-50033
Vogel, C.R.: Computational Methods for Inverse Problem. Frontiers Appl. Math. (2002) ISBN: 0-898715-50-7
Krisch, A.: An Introduction to the Mathematical Theory of Inverse Problems. Applied Mathematical Sciences. Springer, New York (1996)
Chatterjee, S., Litt, J.S.: Online Model Parameter Estimation of Jet Engine Degradation for Autonomous Propulsion Control, NASA/TM—2003-212608,vol. 8 (2003)
lee, G.P.: Performance Deterioration Based on Existing (Historical) Data – JT9D Jet Engine Diagnostics Program, NASA-CR-135448. Pratt and Whitney Aircraft Group
lifeng, W.: Study on Visual Dynamic Modeling Environment of Turbojet Engine. In: 12th Conference on Aerodynamic & Thermodynamic of Propulsion System of China, Sichuan, vol. 9 (2009)
DeCastro, J.A., Litt, J.S., Frederick, D.K.: A Modular Aero-Propulsion System Simulation of a Large Commercial Aircraft Engine”, NASA/TM—2008-215303 (September 2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, L., Zhong, D. (2011). Regularization Method Combined with Parameter Competitive Criterion for Model-Plant Performance Matching of Aircraft Engine. In: Liu, C., Chang, J., Yang, A. (eds) Information Computing and Applications. ICICA 2011. Communications in Computer and Information Science, vol 243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27503-6_90
Download citation
DOI: https://doi.org/10.1007/978-3-642-27503-6_90
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27502-9
Online ISBN: 978-3-642-27503-6
eBook Packages: Computer ScienceComputer Science (R0)