Special Topic: Vibration Identification and Suppression Technology of Aeroengine

Research progress on vibration monitoring and fault diagnosis for aero-engine

  • Minghui HU ,
  • Jinji GAO ,
  • Zhinong JIANG ,
  • Weimin WANG ,
  • Limin ZOU ,
  • Tao ZHOU ,
  • Yunfeng FAN ,
  • Yue WANG ,
  • Jiaxin FENG ,
  • Chenyang LI
Expand
  • 1.State Key Laboratory of High-end Compressor and System Technology,Beijing University of Chemical Technology,Beijing 100029,China
    2.Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education,Beijing University of Chemical Technology,Beijing 100029,China
    3.Beijing Key Laboratory of Health Monitoring and Self-Recovery for High-end Mechanical Equipment,Beijing University of Chemical Technology,Beijing 100029,China
E-mail: gaojinji@263.net

Received date: 2024-01-19

  Revised date: 2024-02-05

  Accepted date: 2024-02-22

  Online published: 2024-02-27

Supported by

National Natural Science Foundation of China(92160203);Youth Talent Support Project(2022-JCJQ-QT-059);Joint Fund of the Ministry of Education of the People’s Republic of China(8091B022203)

Abstract

Aeroengine amalgamates state-of-the-art technologies across diverse domains, serving as a comprehensive manifestation of a nation’s prowess in science and industry. Frequent malfunctions occur due to its complicated structure and harsh service environment. Therefore, it is essential to employ prognostic and health management technology to provide crucial support for aviation safety and reliable operations. As vibration faults constitute a primary failure mode in aeroengine, this paper, grounded in this premise, systematically reviews and analyzes existing vibration monitoring and fault diagnosis for aviation engines both domestically and internationally. The analysis is categorized into three dimensions, covering the application of overall vibration monitoring and diagnostic systems, typical fault characteristics and diagnostic methods, and the overall vibration fault diagnostic technology, including dynamic analysis, signal processing techniques, and relevant technologies such as deep learning. Then, the problems and challenges faced by the existing vibration fault diagnosis of aeroengine are identified. Furthermore, future development goals are provided.

Cite this article

Minghui HU , Jinji GAO , Zhinong JIANG , Weimin WANG , Limin ZOU , Tao ZHOU , Yunfeng FAN , Yue WANG , Jiaxin FENG , Chenyang LI . Research progress on vibration monitoring and fault diagnosis for aero-engine[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(4) : 630194 -630194 . DOI: 10.7527/S1000-6893.2024.30194

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