A Fault Diagnosis Analysis of Afterburner Failure of Aeroengine Based on Fault Tree
Ai He, Qinghua Zeng, You Zhang, Pengfu Xie, Jianping Li, Ming Gao
Abstract
The afterburner is essential for military aeroengines, providing rapid thrust increase during critical maneuvers. However, complex failure mechanisms pose challenges for fault diagnosis and troubleshooting. This study investigates a specific aviation engine’s afterburner engagement principle and typical faults, using fault tree analysis and computational fluid dynamics (CFD). We propose a hybrid diagnostic fault architecture combining traditional observer fault diagnosis with fault trees for online fault diagnosis of critical faults. Simulations and test bench verification confirm the feasibility and effectiveness of our approach, offering valuable insights and guidance for addressing afterburner engagement issues in aviation engines.