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A Sensor-Fault-Tolerant Diagnosis Tool Based on a Quadratic Programming Approach

[+] Author Affiliations
S. Borguet, O. Léonard

University of Liège, Liège, Wallonia, Belgium

Paper No. GT2007-27324, pp. 585-594; 10 pages
doi:10.1115/GT2007-27324
From:
  • ASME Turbo Expo 2007: Power for Land, Sea, and Air
  • Volume 1: Turbo Expo 2007
  • Montreal, Canada, May 14–17, 2007
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 0-7918-4790-X | eISBN: 0-7918-3796-3
  • Copyright © 2007 by ASME

abstract

Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the discrepancies between the model prediction and the measurements are zero-mean, white random variables. However, this assumption is not verified when instrumentation (sensor) faults occur. As a result, the identified health parameters tend to diverge from their actual values which strongly deteriorates the diagnosis. The purpose of this contribution is to blend robustness against sensor faults into a tool for performance monitoring of jet engines. To this end, a robust estimation approach is considered and a Sensor Fault Detection and Isolation module is derived. It relies on a quadratic program to estimate the sensor faults and is integrated easily with the original diagnosis tool. The improvements brought by this robust estimation approach are highlighted through a series of typical test-cases that may be encountered on current turbine engines.

Copyright © 2007 by ASME

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