0
TECHNICAL PAPERS: Gas Turbines: Controls, Diagnostics, and Instrumentation

Hybrid Kalman Filter Approach for Aircraft Engine In-Flight Diagnostics: Sensor Fault Detection Case

[+] Author and Article Information
Takahisa Kobayashi

 ASRC Aerospace Corporation, 21000 Brookpark Road, Cleveland, OH 44135

Donald L. Simon

 U.S. Army Research Laboratory, Glenn Research Center, 21000 Brookpark Road, Cleveland, OH 44135

Engine health degradation is one of these factors, but its contribution to the cause of false alarms is reduced through the health baseline update. Other examples of nonfault-related factors are customer bleeds, horsepower extractions, and dirt washout from fan and compressors.

J. Eng. Gas Turbines Power 129(3), 746-754 (Nov 17, 2006) (9 pages) doi:10.1115/1.2718572 History: Received November 16, 2006; Revised November 17, 2006

In this paper, a diagnostic system based on a uniquely structured Kalman filter is developed for its application to in-flight fault detection of aircraft engine sensors. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the diagnostic system to be updated, through a relatively simple process, to the health condition of degraded engines. Through this health baseline update, the diagnostic effectiveness of the in-flight sensor fault detection system is maintained as the health of the engine degrades over time. The performance of the sensor fault detection system is evaluated in a simulation environment at several operating conditions during the cruise phase of flight.

FIGURES IN THIS ARTICLE
<>
Copyright © 2007 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Figure 5

Histograms of maximum WSSR values for 300 health condition mismatch cases at cruise

Grahic Jump Location
Figure 1

Engine health degradation

Grahic Jump Location
Figure 2

Process of health baseline update

Grahic Jump Location
Figure 3

Baseline update using estimated health degradation

Grahic Jump Location
Figure 4

Overall architecture of the in-flight fault detection system

Grahic Jump Location
Figure 6

Time history of transient inputs

Grahic Jump Location
Figure 7

WSSR responses for transient scenario 2

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In