In this study a model-based procedure exploiting analytical redundancy for the detection and isolation of faults of a gas turbine system is presented. The diagnosis scheme is based on the generation of so-called ”residuals” that are errors between estimated and measured variables of the process. The work is completed under both noise-free and noisy conditions. Residual analysis and statistical tests are used for fault detection and isolation, respectively. The final section shows how the actual size of each fault can be estimated using a multi-layer perceptron neural network used as a non-linear function approximator. The proposed fault detection and isolation tool has been tested on a single-shaft industrial gas turbine model.

Identification and fault diagnosis of a simulated model of an industrial gas turbine

SIMANI, Silvio;
1999

Abstract

In this study a model-based procedure exploiting analytical redundancy for the detection and isolation of faults of a gas turbine system is presented. The diagnosis scheme is based on the generation of so-called ”residuals” that are errors between estimated and measured variables of the process. The work is completed under both noise-free and noisy conditions. Residual analysis and statistical tests are used for fault detection and isolation, respectively. The final section shows how the actual size of each fault can be estimated using a multi-layer perceptron neural network used as a non-linear function approximator. The proposed fault detection and isolation tool has been tested on a single-shaft industrial gas turbine model.
1999
Fault diagnosis; Identification; Observers; Kalman filtering; Gas turbines
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1189580
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact