Supervision of performance in gas turbine applications is important 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 good diagnosis performance it is important to have tests which are based on models with high accuracy. A main contribution of the thesis is a systematic design procedure to construct a fault detection and isolation (FDI) system which is based on complex nonlinear models. These models are preliminary used for simulation and performance evaluations. Thus, is it possible to use these models also in the FDI-system and which model parts are necessary to consider in the test design? 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 models are carefully selected. These equations are then used to implement a Constant Gain Extended Kalman filter (CGEKF) based test quantity. The number of equations and variables which the test quantity is based on is significantly reduced compared to the original reference model. The test quantity is used in the FDI-system to supervise the performance and the turbine inlet temperature which is used in the controller. 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. When the FDI-system is augmented with more test quantities it is possible to diagnose sensor and actuator faults at the same time the performance is supervised. Slow varying sensor and actuator bias faults are difficult diagnose since they appear in a similar manner as the performance deterioration, but the FDI-system has the ability to detect these faults. Finally, the proposed model based design procedure can be considered when an FDI-system of an industrial gas turbine is constructed.iii Populärvetenskaplig sammanfattning Diagnostik och prestandaövervakning förekommer inom många industriella applikationer. Detta område är viktigt att beakta för att: (i) upprätthålla hög tillförlitlighet, (ii) undvika onödig belastning på komponenter, (iii) minimera energiförbrukningen, och (iv) effektivt kunna planera underhåll. Eftersom prestandan i en applikation oftast inte är direkt mätbar behövs metoder för att kunna skatta dessa prestandaparametrar utifrån kända mätsignaler. Detta kan vara svårt eftersom: (i) sambandet mellan mätsig-naler och prestandaparametrar kan vara komplicerat, (ii) mätsignaler innehåller brus, och (iii) mätsignaler kan vara opålitliga och visa ett felaktigt värde. Dessa aspekter bör beaktas när ett diagnos-och övervakningssystem utvecklas. Eftersom många system är komplexa kan det vara nödvändigt att ha effektiva och automatiserade metoder för att skatta prestanda och bestämma diag...