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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 10

Intelligent fault diagnosis of aero-engine bearings under variable operating conditions based on deep learning and feature condensation

Liu Han
Liu Qinming
Ye Chunming
Wang Yujie
Business School, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2025.04.0088

Abstract

Bearings are core components of aero-engine systems, and their fault diagnosis is crucial. To tackle the challenge that fault diagnosis models based on original training datasets cannot directly apply to new working conditions of aero-engine bearings under extremely complex and variable scenarios, researchers developed a high-precision intelligent fault diagnosis method. First, they built an independent component analysis module by integrating a one-dimensional variance-difference convolutional neural network and a mobile network attention mechanism to effectively extract fault features. Then, they optimized the gated recurrent unit module with a dynamic weight-controlled starling optimization algorithm, thus achieving accurate fault state identification. Case studies showed that this method achieved a 100% fault diagnosis accuracy rate under variable working conditions and exhibited excellent noise resistance. These results confirm that the method effectively solves the problem of fault diagnosis for aero-engine bearings under variable working conditions.

Foundation Support

国家自然科学基金资助项目(71632008,71840003)
上海市2021度"科技创新行动计划"宝山转型发展科技专项项目(21SQBS01404)
上海理工大学科技发展项目(2020KJFZ038)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.04.0088
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 10

Publish History

[2025-06-17] Accepted Paper

Cite This Article

刘涵, 刘勤明, 叶春明, 等. 基于深度学习和特征凝练的变工况航空发动机轴承智能故障诊断 [J]. 计算机应用研究, 2025, 42 (10). (2025-06-19). https://doi.org/10.19734/j.issn.1001-3695.2025.04.0088. (Liu Han, Liu Qinming, Ye Chunming, et al. Intelligent fault diagnosis of aero-engine bearings under variable operating conditions based on deep learning and feature condensation [J]. Application Research of Computers, 2025, 42 (10). (2025-06-19). https://doi.org/10.19734/j.issn.1001-3695.2025.04.0088. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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