Gas path fault diagnosis for gas turbine engines with fully operating regions using mode identification and model matching

Abstract

Gas path fault diagnosis is key to improving the reliability and safety of gas turbine engines. Flexible operating conditions bring obstacles to performing accurate gas path performance analysis. Most of the existing methods are developed for specific operating conditions, which are difficult to adapt to fully operating regions. The operating mode identification and targeted diagnostic model matching are effective technologies to solve the gas path fault diagnosis under fully operating regions, which improves diagnostic accuracy and efficiency. The fully operating regions are classified into four typical operating modes, and the targeted diagnostic models are matched according to the mode features. For the typical start-stop state and high dynamic state, the small deviation diagnostic model and transient diagnostic model are established and verified by real fault cases. The small deviation diagnostic model based on boundary parameters reduces the influences of operating conditions on diagnostic results, it accurately monitors the health states. The transient diagnostic model driven by the dynamic model and a designed hybrid solution algorithm markedly improves diagnostic accuracy and efficiency. It shows better performance for the mixed gas path fault modes, more stable diagnostic results, and higher diagnostic efficiency. The proposed technical framework provides an effective way for the fault diagnosis of gas turbine engines under fully operating regions.