航空学报 > 2022, Vol. 43 Issue (9): 625574-625574   doi: 10.7527/S1000-6893.2021.25574

民用航空发动机故障诊断与健康管理现状、挑战与机遇Ⅱ: 地面综合诊断、寿命管理和智能维护维修决策

曹明1,2, 王鹏1,2, 左洪福3, 曾海军1, 孙见忠3, 杨卫东4, 魏芳1, 陈雪峰5   

  1. 1. 中国航发商用航空发动机有限责任公司, 上海 201109;
    2. 上海交通大学 航空航天学院, 上海 200240;
    3. 南京航空航天大学 能源与动力学院, 南京 210016;
    4. 复旦大学 航空航天数据研究中心, 上海 200433;
    5. 西安交通大学 机械工程学院, 西安 710049
  • 收稿日期:2021-03-26 修回日期:2021-05-11 出版日期:2022-09-15 发布日期:2021-08-25
  • 通讯作者: 曹明,E-mail:fanfeilong369@126.com E-mail:fanfeilong369@126.com
  • 基金资助:
    国家科技重大专项(2017-Ⅳ-0008-0045)

Current status, challenges and opportunities of civil aero-engine diagnostics & health management Ⅱ: Comprehensive off-board diagnosis, life management and intelligent condition based MRO

CAO Ming1,2, WANG Peng1,2, ZUO Hongfu3, ZENG Haijun1, SUN Jianzhong3, YANG Weidong4, WEI Fang1, CHEN Xuefeng5   

  1. 1. AECC Commercial Aircraft Engine Co. Ltd, Shanghai 201109, China;
    2. School of Aeronautics and Astronautics, Shanghai Jiaotong University, Shanghai 200240, China;
    3. School of Energy & Power, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    4. Research Center for Dataology and Data Schience, Fudan University, Shanghai 200433, China;
    5. School of Mechanical Engineering, Xian Jiaotong University, Xi'an 710049, China
  • Received:2021-03-26 Revised:2021-05-11 Online:2022-09-15 Published:2021-08-25
  • Supported by:
    National Science and Technology Major Project (2017-Ⅳ-0008-0045)

摘要: 基于民用航空发动机健康管理(EHM)的需求及发展目标, 从CBM+全流程的角度分析民用航空发动机健康管理系统应用现状及行业发展趋势, 进而总结民用航空发动机健康管理的应用现状及差距、挑战, 并指出未来国内需要重点关注的民用发动机EHM研发方向。针对各个EHM功能模块的需求、差距、解决方案进行了深入论证分析, 重点讨论了民用发动机EHM"下游"3个模块: 地面综合诊断、寿命管理和智能视情维护维修决策的需求、必要性、现状及未来发展趋势和热点技术。

关键词: 航空发动机健康管理系统, 故障融合决策, 深度学习, 知识图谱, 数字孪生, 寿命管理, 智能视情维护维修

Abstract: Based on a comprehensive coverage of the civil aero-Engine Health Management (EHM) needs and goals, this research and development review first analyzes the current status quo & industry trends from the perspectives of the full blown Condition Based Maintenance Plus (CBM+) process, then addresses the challenges and gaps, and points out the critical paths for the future EHM research and development. Furthermore, this research and development review provides in-depth discussions on needs, gaps, and potential EHM solutions/future developments of the three "down-stream" EHM development modules: off-board comprehensive diagnostics, engine life management, intelligent condition based mro (maintenance, repair, overhaul).

Key words: aero engine health management system, diagnostics based on data fusion, deep learning, knowledge graph, digital twin, life management, intelligent condition based MRO

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