NDLI: Fault diagnosis in gas turbine engines using fuzzy logic

Content Provider	IEEE Xplore Digital Library
Author	Gayme, D. Menon, S. Ball, C. Mukavetz, D. Nwadiogbu, E.
Copyright Year	2003
Description	Author affiliation: Honeywell Engines, Syst. & Services, Minneapolis, MN, USA (Gayme, D.; Menon, S.)
Abstract	This paper describes a fuzzy logic-based method of fault detection and diagnosis in gas turbine engines. The fuzzy logic rule base is derived using heuristics based on designed experiments and flight data. The method is evaluated using model-based residuals and calculated values as inputs. The efficacy of the system is demonstrated using flight data. This paper describes how to augment a limited number of input parameters by combining them with the rates of change of the normal input parameters and other derived parameters. This augmented parameter set enables a better estimate of the prediction horizon for diagnosis. The paper also presents a case study where high-pressure spool deterioration is detected about two months prior to engine failure. Although, the system is demonstrated using the example of high pressure spool deterioration it can be applied to engine failures with similar characteristics.
Sponsorship	Syst., Man & Cybernetics Soc. IEEE
Starting Page	3756
Ending Page	3762
File Size	520838
Page Count	7
File Format	PDF
ISBN	0780379527
ISSN	1062922X
DOI	10.1109/ICSMC.2003.1244473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Turbines Engines Fuzzy logic Fault detection Costs Neural networks Testing Air safety Delay
Content Type	Text
Resource Type	Article

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