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A Data-Driven Diagnosis Method for Bearing Fault Using Harmonics of Stator Current
ID：67 View Protection：ATTENDEE Updated Time：2024-08-15 10:48:34 Hits：305 Oral Presentation

Start Time：Pending（Asia/Shanghai）

Duration：Pending

Session：No Session »

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Abstract
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.
Keywords
data-drive,motor bearing fault diagnosis,current signal,harmonics,asynchronous motor
Speaker
Qian Wu
Mr. Southwest Jiaotong University

Submission Author
Qian Wu Southwest Jiaotong University
Hu Cao Southwest Jiaotong University
Runfang Tong Southwest Jiaotong University
Bin Gou Southwest Jiaotong University
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Important Date

  • Conference Date

    Nov 06

    2024

    to

    Nov 08

    2024

  • Sep 15 2024

    Draft paper submission deadline

  • Nov 08 2024

    Registration deadline

Sponsored By
Huazhong University of Science and Technology
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