ARX Linear Model Set-Up for Fault Diagnosis of Gas Turbine Sensors PUBLIC ACCESS

[+] Author Affiliations
R. Bettocchi, P. R. Spina

Università di Ferrara, Ferrara, Italy

Paper No. 97-GT-027, pp. V004T15A004; 9 pages
  • ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition
  • Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar Award
  • Orlando, Florida, USA, June 2–5, 1997
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-7871-2
  • Copyright © 1997 by ASME


The diagnosis of gas turbine sensor faults requires models of the system to calculate estimates of the measured output system variables.

The model set-up phase is of great importance since the reliability of the diagnostic tool depends on the model accuracy.

In the paper two different methodologies of I/O linear model set-up are analyzed and compared to find the more simple and general one.

The first methodology consists in obtaining the I/O linear models by directly linearizing the physical laws (system modeling).

The second one uses statistical methods (system identification) to calculate model parameters from time series data measured on the machine. The models used are of the ARX (Auto Regressive with eXternal input) type. The number of models and the measured variables correlated by each of them have been determined in order to obtain unambiguous fault signatures for each sensor.

The system identification method proves to be more suitable to the system modeling because of its greater simplicity in the fault diagnosis application.

Copyright © 1997 by ASME
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