In this work, a model--based procedure exploiting the analytical redundancy principle for the detection and isolation of the input--output sensor faults on a gas turbine simulated process is presented. The contribution of the paper consists of exploiting an identification scheme in connection with Kalman filter design procedure for diagnostic purposes. Thus, black--box modelling and output estimation approach to fault diagnosis are in particular advantageous in terms of solution complexity and performance achieved. In order to verify the effectiveness of the proposed FDI strategy, it has been applied to the simulation data of a single--shaft industrial gas turbine model in the presence of measurement and modelling errors. Hence, extensive simulations of the gas turbine simulator are the tools for assessing the capabilities of the developed FDI scheme, when compared also with different model--based and data--driven fault diagnosis methods.

A System Identification Approach for the FDI of an Industrial Gas Turbine Model

SIMANI, Silvio;
2009

Abstract

In this work, a model--based procedure exploiting the analytical redundancy principle for the detection and isolation of the input--output sensor faults on a gas turbine simulated process is presented. The contribution of the paper consists of exploiting an identification scheme in connection with Kalman filter design procedure for diagnostic purposes. Thus, black--box modelling and output estimation approach to fault diagnosis are in particular advantageous in terms of solution complexity and performance achieved. In order to verify the effectiveness of the proposed FDI strategy, it has been applied to the simulation data of a single--shaft industrial gas turbine model in the presence of measurement and modelling errors. Hence, extensive simulations of the gas turbine simulator are the tools for assessing the capabilities of the developed FDI scheme, when compared also with different model--based and data--driven fault diagnosis methods.
2009
9789633113691
Fault detection and isolation; system identification; kalman filter; residual generation; gas turbine
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/533431
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