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Multimodal MOE for fault diagnosis of external gear pumps
编号：21 访问权限：仅限参会人 更新：2025-11-10 10:55:06 浏览：45次 口头报告

报告开始：2025年11月22日 17:20（Asia/Shanghai）

报告时间：20min

所在会场：[S2] Parallel Session 2 [S2-1] Parallel Session 2-22 PM

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摘要
The external gear pump, as the core component of the fuel system in aircraft engines, is crucial for its reliable operation. Therefore, conducting effective fault diagnosis is of great significance. In view of the limitations of methods based on single-modality data, and the problem that existing methods for integrating multimodal data fail to fully exploit the interaction between modalities, this paper proposes a new fault diagnosis method. Firstly, masking is applied to the pressure and vibration signals based on the physical effect of the gear pump, and features are extracted using a fully convolutional network(FCN). Secondly, based on the theory of partial information decomposition(PID), a Mixture of Experts(MOE) is constructed to depict the interaction relationship between different modalities. Finally, the outputs of each expert are fused through a re-weighting mechanism to obtain the final prediction result. Experiments on the gear pump dataset show that the proposed method has superior diagnostic performance.
关键词
Fault Diagnosis
报告人
Jinyang Wang
Mr. Hefei University of Technology

稿件作者
Jinyang Wang Hefei University of Technology
Xiaochuan Li Hefei University of Technology
Juan Xu Hefei University of Technology
Chuan Li Chongqing Technology And Business University
David Mba Birmingham City University
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重要日期

  • 会议日期

    11月21日

    2025

    至

    11月23日

    2025

  • 10月20日 2025

    初稿截稿日期

  • 11月23日 2025

    注册截止日期

主办单位
IEEE Instrumentation and Measurement Society
South China University of Technology
承办单位
South China University of Technology
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