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A Data-Driven Diagnosis Method for Bearing Fault Using Harmonics of Stator Current
编号：67 访问权限：仅限参会人 更新：2024-08-15 10:48:34 浏览：122次 口头报告

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摘要
Most of the diagnosis methods for the asynchronous motor bearing faults are based on vibration signals. However, vibration signals require additional sensors and extra space for installation. In this paper, a data-driven method for asynchronous motor bearing fault diagnosis based on stator current is proposed. The harmonics of stator current are extracted as features after processing by wavelet denoising and quasi-synchronous sampling algorithm, and the mapping relationship between features and labels is obtained by random vector functional link. The experimental test results show that the algorithm can accurately distinguish healthy bearings and inner race faulty bearings or outer race faulty bearings under different working conditions.
关键词
data-drive,motor bearing fault diagnosis,current signal,harmonics,asynchronous motor
报告人
Qian Wu
Mr. Southwest Jiaotong University

稿件作者
Qian Wu Southwest Jiaotong University
Hu Cao Southwest Jiaotong University
Runfang Tong Southwest Jiaotong University
Bin Gou Southwest Jiaotong University
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重要日期

  • 会议日期

    11月06日

    2024

    至

    11月08日

    2024

  • 09月15日 2024

    初稿截稿日期

  • 11月08日 2024

    注册截止日期

主办单位
Huazhong University of Science and Technology
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