Estimation of multiple faults in aircraft gas-turbine engines

Author

Sarkar, Soumik ; Rao, Chinmay ; Ray, Asok

Author_Institution

Dept. of Mech. Eng., Pennsylvania State Univ., University Park, PA, USA

fYear

2009

fDate

10-12 June 2009

Firstpage

216

Lastpage

221

Abstract

This paper presents estimation of multiple faults in aircraft gas-turbine engines, based on a statistical pattern recognition tool called symbolic dynamic filtering (SDF). The underlying concept is built upon statistical analysis of evidences to estimate anomalies in multiple critical parameters of the engine system; it also presents a framework for sensor information fusion. The fault estimation algorithm is validated by numerical simulation on the NASA C-MAPSS test-bed of commercial aircraft engines.

Keywords

condition monitoring; fault diagnosis; gas turbines; jet engines; pattern recognition; sensor fusion; statistical analysis; NASA C-MAPSS test-bed; aircraft gas-turbine engines; anomalies estimation; health monitoring; multiple critical parameters; multiple fault estimation algorithm; sensor information fusion; statistical pattern recognition tool; symbolic dynamic filtering; turbofan engine; Aircraft propulsion; Engines; Filtering; NASA; Numerical simulation; Pattern recognition; Sensor fusion; Sensor systems; Statistical analysis; Testing; Aircraft Propulsion; Gas Turbine Engines; Multiple fault estimation; Statistical Pattern Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2009. ACC '09.

Conference_Location

St. Louis, MO

ISSN

0743-1619

Print_ISBN

978-1-4244-4523-3

Electronic_ISBN

0743-1619

Type

conf

DOI

10.1109/ACC.2009.5159981

Filename

5159981