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TECHNICAL PAPERS: Gas Turbines: Controls, Diagnostics, and Instrumentation

Application of Fuzzy Logic for Fault Isolation of Jet Engines

[+] Author and Article Information
R. Ganguli

Department of Aerospace Engineering, Indian Institute of Science, Bangalore 560 012, India

J. Eng. Gas Turbines Power 125(3), 617-623 (Aug 15, 2003) (7 pages) doi:10.1115/1.1470481 History: Received December 01, 2000; Revised March 01, 2001; Online August 15, 2003
Copyright © 2003 by ASME
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References

Figures

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Fingerprint chart showing change in fuel flow (WF) for a module efficiency decrease of −2%
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Impact of coupling factor on high-pressure compressor (HPC) fault isolation success rate with different sensor suites
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Impact of coupling factor on low-pressure compressor (LPC) fault isolation success rate with different sensor suites
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Fingerprint chart showing change in exhaust gas temperature (EGT) for a module efficiency decrease of −2%
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Fingerprint chart showing change in high-spool rotor speed (N2) for a module efficiency change of −2%
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Fingerprint chart showing change in low-spool rotor speed (N1) for a module efficiency change of −2%
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Gaussian functions defining linguistic measures for fuzzy set for exhaust gas temperature (EGT) delta
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Gaussian functions defining linguistic measures for fuzzy sets for fuel flow (WF) delta
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Gaussian functions defining linguistic measures for fuzzy sets for high-spool rotor speeds (N2) delta
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Gaussian functions defining linguistic measures for fuzzy set for low-spool rotor speeds (N1) delta
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Success rate in fault isolation for uncertainty levels different from design point (= 0)
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Success rate in high-pressure compressor (HPC) fault isolation with additional sensors and increasing levels of uncertainty
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Success rate in low-pressure compressor (LPC) fault isolation with additional sensors and increasing levels of uncertainty
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Impact of coupling factor on fan (FAN) fault isolation success rate with different sensor suites

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