%A CAO Ming, HUANG Jinquan, ZHOU Jian, CHEN Xuefeng, LU Feng, WEI Fang %T Current status, challenges and opportunities of civil aero-engine diagnostics & health management Ⅰ: Diagnosis and prognosis of engine gas path, mechanical and FADEC %0 Journal Article %D 2022 %J Acta Aeronautica et Astronautica Sinica %R 10.7527/S1000-6893.2021.25573 %P 625573-625573 %V 43 %N 9 %U {https://hkxb.buaa.edu.cn/CN/abstract/article_18753.shtml} %8 2022-09-15 %X The engineering advancements during the last two decades have presented opportunities as well as challenges for the Engine Health Management (EHM) system development of civil aero-engines. This R&D review provides an in-depth discussion on EHM needs, gaps and potential solutions/future R&D development directions, focusing on the "up-stream" EHM development modules: Engine gas path diagnostics and prognostics, mechanical diagnostics and prognostics, FADEC diagnostics and prognostics. Results shows the Unscented Kalman Filter (UKF) method and deep-learning neural networks have shown promises on improving the engine gas path diagnostics accuracy; composite fans have found widespread applications in turbo-fan engines; powder metallurgy has seen more and more applications on fabricating aero-engine parts with complex shapes; the accuracies of metal particle sensing technologies have witnessed significant improvements, with technology readiness level matching the aero-engine needs, and paved the way for fusion diagnostics with vibration signal. The result also show that electrification and intelligentization trends of FADEC system presents new challenges for the diagnostics of the traditionally centralized control architecture.