A Comprehensive Review of Key Technologies for Enhancing the Reliability of Aero-Engines

Abstract

Aero-engines are highly complex machines, and their reliability and lifespan directly impact flight safety. As a result, aero-engine reliability has become a significant research field. This paper aims to comprehensively summarize the progress in aero-engine reliability research. First, we analyzed the existing structures of aircraft engines, as well as the current research on reliability and commonly used estimation methods. Second, we reviewed the techniques employed for monitoring operational status and diagnosing faults in aircraft engines. Third, we summarized the optimization methods frequently used in fault diagnosis and lifespan prediction. Fourth, we conducted a bibliometric analysis. Finally, we identified potential challenges for future research. Based on our literature review, we found that: 1) mathematical modeling-based and data-driven approaches are currently the most commonly used methods for performance monitoring; 2) neural networks and deep learning are the most popular methods for fault diagnosis and lifespan prediction; 3) the bibliometric analysis reveals that China’s interest in aero-engine reliability research techniques is higher than that of other countries; and 4) further development is needed in the areas of overall system reliability, real-world usage scenario studies, and advanced simulation and modeling.

Keywords

• Aero-engine
• reliability models and algorithms
• performance monitoring
• fault diagnosis
• life prediction
• bibliometrics