Forecasting the health of gas turbine components through an integrated performance-based approach

In this study, we present an integrated method for detecting and forecasting the health of gas turbine components as degraded over time. An advanced model-based real time performance adaptation approach is developed for detecting the degradation of engine components via a dynamic engine model that is built in Simulink. The detected health parameters of the engine component are then implemented in a discrete window-based analysis by a regression method in order to forecast their evolution. The proposed approach is tested for an engine with increased flexibility that characterizes modern gas turbine operations. The results demonstrate the promising capabilities of our advanced proposed method for accurate and efficient detection and forecast of the health of gas turbine compressors as degraded over time.