The supervision of performance in gas turbine applications is crucial in order to achieve: (i) reliable operations, (ii) low heat stress in components, (iii) low fuel consumption, and (iv) efficient overhaul and maintenance. To obtain a good diagnosis of performance it is important to have tests which are based on models with high accuracy. A main contribution is a systematic design procedure to construct a fault detection and isolation (FDI) system for complex nonlinear models. To fulfill the requirement of an automated design procedure, a thermodynamic gas turbine package (GTLib) is developed. Using the GTLib framework, a gas turbine diagnosis model is constructed where component deterioration is introduced. In the design of the test quantities, equations from the developed diagnosis model are carefully selected. These equations are then used to implement a constant gain extended Kalman filter (CGEKF)-based test quantity. The test quantity is used in the FDI-system to supervise the performance and in the controller to estimate the flame temperature. An evaluation is performed using experimental data from a gas turbine site. The case study shows that the designed FDI-system can be used when the decision about a compressor wash is taken. Thus, the proposed model-based design procedure can be considered when an FDI-system of an industrial gas turbine is constructed.

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