S-Transform Based Time–Frequency Analysis Tool with Application to Detection Bearing Fault
ID:81 View Protection:ATTENDEE Updated Time:2021-08-19 16:15:53 Hits:428 Oral Presentation

Start Time:Pending(Asia/Shanghai)

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Abstract
The actual measured vibration signal of the defective mechanical equipment is generally non-stationary. Extracting effective and useful features from non-stationary signals has always been an important research topic in fault diagnosis. A novel time–frequency analysis method, called time-reassigned synchrosqueezing extracting S-transform has been proposed in this study. Compared with traditional time-frequency analysis methods, the method can not only extract the useful information of non-stationary signals well, and obtain a more concentrated time-frequency representation, but also has better noise robustness and lower time consumption. The analysis of numerical signals verified the great performance of this method. Finally, time-reassigned synchrosqueezing extracting S-transform (TSSEST) is applied to perform the spectral decomposition of a bearing fault data. The numerical and experimental signals are used to show the effectiveness of our method.
Keywords
S-Transform; time–frequency analysis; Fault Detection;
Speaker
Zhenghao Cui
University of Jinan

Submission Author
Zhenghao Cui University of Jinan
Gang Yu University of Jinan
Wei Tian University of Jinan
Haoran Dong University of Jinan
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Important Date
  • Conference Date

    Nov 01

    2022

    to

    Nov 03

    2022

  • Oct 30 2022

    Draft paper submission deadline

  • Nov 09 2022

    Registration deadline

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