In this paper, common faults in main components of an industrial two-shaft gas turbine are simulated, and the fault signatures are determined in both part and full-load conditions. As fouling and erosion are the most important and effective causes of performance deterioration in gas turbines (GTs), the effects of these faults on the performance of all three main components including compressor, gas generator turbine, and power turbine are studied and their effects on the overall efficiency of the whole system are analyzed. In this study, the faults simulation is performed by changing the health parameters (flow capacity and isentropic efficiency) of each GT components via modification of the compressor and turbines characteristic curves. The results obtained from the compressor fouling simulation are validated against the published experimental data; the validation results represent acceptable simulation accuracy in estimation of the measurement parameters deviation. Moreover, the fault signatures are determined in full-load conditions, and the effects of the examined faults on the main GT parameters are analyzed; in this way, the key measurement parameters in identification of these faults are introduced. Finally, in order to identify the fault signatures in part-load conditions, the fault implantation process is performed for each 10% reduction in gas turbine loads. Simulation results demonstrate that the fault signatures have different sensitivity to load variations, and thus, these are in general a function of the GT loading conditions.

This paper presents the metaheuristic design and optimization of fuzzy-based gas turbine engine (GTE) fuel flow controller by means of a hybrid invasive weed optimization/particle swarm optimization (IWO/PSO) algorithm as an innovative guided search technique. In this regard, first, a Wiener model for the GTE as a block-structured model is developed and validated against experimental data. Subsequently, because of the nonlinear nature of GTE, a fuzzy logic controller (FLC) strategy is considered for the engine fuel system. For this purpose, an initial FLC is designed and the parameters are then tuned using a hybrid IWO/PSO algorithm where the tuning process is formulated as an engineering optimization problem. The fuel consumption, engine safety, and time response are the performance indices of the defined objective function. In addition, two sets of weighting factors for objective function are considered, whereas in one of them savings in fuel consumption and in another achieving a short response time for the engine is a priority. Moreover, the optimization process is performed in two stages during which the database and the rule base of the initial FLC are tuned sequentially. The simulation results confirm that the IWO/PSO-FLC approach is effective for GTE fuel controller design, resulting in improved engine performance as well as ensuring engine protection against physical limitations.