Comprehensive review of gas turbine fault diagnostic strategies

Gas turbine engines are predominant prime movers in the transport and energy sectors, serving diverse applications ranging from power generation to aviation propulsion. Given their critical role, ensuring reliable and efficient operation is of paramount significance. However, unforeseen faults can compromise their reliability, resulting in reduced efficiency, increased maintenance costs, and potentially catastrophic failures. This review paper explores the realm of gas turbine health management, focusing on fault diagnosis, which is essential for ensuring the reliability and performance of gas turbine systems in various aviation and industrial sectors. To bridge the identified gaps in earlier review articles, this paper provides a holistic framework for classifying and analyzing the full spectrum of gas-turbine faults, including gas-path, mechanical, combustion, sensor, actuator, and composite failures. Additionally, it presents a comprehensive review of proposed diagnostic approaches, including model-based, data-driven, and advanced hybrid techniques developed for each category of faults. Additionally, a structured taxonomy for hybrid methods is established. Furthermore, simulation platforms and publicly available datasets are reviewed for the first time, highlighting both their advantages and limitations. This review aims to help researchers and practitioners understand the current state-of-the-art developments in this emerging field. Through an examination of gas turbine diagnosis techniques, the paper identifies patterns and trends in the literature, highlights the existing gaps and limitations, and offers recommendations for future research directions in this realm.