Technical Papers
Feb 6, 2012

Performance Diagnosis for Turbojet Engines Based on Flight Data

Publication: Journal of Aerospace Engineering
Volume 27, Issue 1

Abstract

The purpose of the current study is to improve the flight data analysis in the existing program of flight operations quality assurance (FOQA) of the airlines. The goal is to detect any potential problems related to engine health. The exhaust gas temperature (EGT) is the primary parameter in performance monitoring and diagnosis. Performance reference models are obtained through fuzzy-logic modeling. As the first example in the present paper, the potential problems and abnormal conditions can be diagnosed after a comparative analysis with the reference model for a four-engine jet freighter. This paper also uses a twin-jet passenger transport as the second example to illustrate the concept of relative efficiency for engine components. The sensitivity derivatives of EGT with respect to the operational variables indicate that the performance of these two engines has been declining because of aging.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

This research project is sponsored by a grant, NSC 101-2221-E-157-002, from the National Science Council (NSC). The accomplishment in this project is part of the requirements set by the Aviation Safety Council (ASC), Taiwan (R.O.C.).

References

Aviation Safety Council. (2009). “Uni Airways, Flight B7652.” Factual Data Collection Group Rep. ASC-AFR-09-10-001, New Taipei City, Taiwan.
Chang, R. C., Ye, C. E., Lan, C. E., and Guan, W. L. (2010). “Stability characteristics for transport aircraft response to clear-air turbulence.” J. Aerosp. Eng., 23(3), 197–204.
DePold, H. R., and Gass, F. D. (1999). “The application of expert systems and neural networks to gas turbine prognostics and diagnostics.” J. Eng. Gas Turbines Power, 121(4), 607–612.
Ganguli, R. (2002a). “A fuzzy logic intelligent system for gas turbine module and system fault isolation.” J. Propul. Power, 18(2), 440–447.
Ganguli, R. (2002b). “Noise and outlier removal from jet engine health signals using weighted FIR median hybrid filters.” Mech. Syst. Signal Process., 16(6), 967–978.
Ganguli, R. (2003a). “Application of fuzzy logic for fault isolation of jet engines.” J. Eng. Gas Turbines Power, 125(3), 617–623.
Ganguli, R. (2003b). “Jet engine gas-path measurement filtering using center weighted idempotent median filters.” J. Propul. Power, 19(5), 930–937.
Ganguli, R., and Dan, B. (2004). “Trend shift detection in jet engine gas path measurement using cascaded recursive median filter with gradient and Laplacian edge detector.” J. Eng. Gas Turbine Power, 126(1), 55–61.
Kobayashi, T., and Simon, D. L. (2003). “Application of a bank of Kalman filters for aircraft engine fault diagnostics.” NASA TM 2003-212526, National Aeronautics and Space Administration Center for Aerospace Information, Hanover, MD.
Lan, C. E., Bianchi, S., and Brandon, J. M. (2008). “Estimation of nonlinear aerodynamic roll models for identification of uncommanded rolling motions.” J. Aircr., 45(3), 916–922.
Lan, C. E., and Brandon, J. M. (2003). “Development of nonlinear aerodynamic models from flight data and evaluation of tabulated aerodynamic models.” AIAA 2003-5696, American Institute of Aeronautics and Astronautics, Reston, VA.
Lan, C. E., Chang, R. C., and Guan, W. L. (2006). “Evaluation of structural integrity of transport aircraft based on flight data.” J. Aeronaut. Astronaut. Aviat. Ser. A, 38(3), 159–166.
Lee, Y. N., and Lan, C. E. (2003). “Estimation of engine integrity through fuzzy logic modeling.” AIAA 2003-6817, American Institute of Aeronautics and Astronautics, Reston, VA.
Mattingly, J. D., Heiser, W. H., and Pratt, D. T. (2002). Aircraft engine design, 2nd Ed., American Institute of Aeronautics and Astronautics, Reston, VA.
Sampath, S., and Singh, R. (2006). “An integrated fault diagnostics model using genetic algorithm and neural networks.” J. Eng. Gas Turbines Power, 128(1), 49–56.
Takagi, T., and Sugeno, M. (1985). “Fuzzy identifications of systems and its applications to modeling and control.” IEEE Trans. Syst. Man Cybern., 15(1), 116–132.
Tumer, I., and Bajwa, A. (1999). “Learning about how aircraft engines work and fail.” AIAA-99-2850, Ames Research Center, National Aeronautics and Space Administration (NASA), Mountain View, CA.
Verma, R., Roy, N., and Ganguli, R. (2006). “Gas turbine diagnostics using a soft computing approach.” Appl. Math. Comput., 172(2), 1342–1363.
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.” J. Eng. Gas Turbines Power, 125(4), 917–924.
Zadeh, L. A. (1973). “Outline of a new approach to the analysis of complex systems and decision processes.” IEEE Trans. Syst. Man Cybern., 3(1), 28–44.

Information & Authors

Information

Published In

Go to Journal of Aerospace Engineering
Journal of Aerospace Engineering
Volume 27Issue 1January 2014
Pages: 9 - 15

History

Received: May 24, 2011
Accepted: Jan 18, 2012
Published online: Feb 6, 2012
Published in print: Jan 1, 2014

Permissions

Request permissions for this article.

Authors

Affiliations

Ray C. Chang [email protected]
Associate Professor, Aviation Mechanical Engineering Dept., China Univ. of Science and Technology, Hsin-Chu 312, Taiwan, Republic of China. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share