21 / 2021-03-16 21:19:52
Generalized Horizontal Multi-synchrosqueezing Transform
Nonstationary signal; Time-frequency analysis (TFA); Synchrosqueezing transform (SST); Fault diagnosis
Final Paper
Wenjie Bao / Shanghai Jiaotong University
Fucai Li / Shanghai Jiaotong University
Nan Ye / Marine Design & Research Institute of China
Zhen Liu / Shanghai Jiaotong University
Zhihao Chen / Shanghai Jiaotong University
Gangao Zuo / Shanghai Jiaotong University
Time-frequency analysis (TFA) is one of the most critical tools to process nonstationary signals for a long time. However, classical TFA methods is invalid for the transient signal with sharply frequency-varying features. This paper proposes a new TFA method termed as the generalized horizontal multi-synchrosqueezing transform (GHMST) to deal with the transient signal. Firstly, a frequency-domain signal model is constructed and expanded to a high-order Taylor expression. Then, based on this expression, the explicit formula of the high-order group delay (GD) is derived with a concise manner. Finally, the time-frequency energy is reassigned to this estimated GD through an iterative procedure. Meanwhile, the corresponding algorithm implementation is programmed to demonstrate the feasibility of the GHMST. The numerical validation shows the superiority of the proposed method in analysing impulse-like signal compared with other advanced TFA methods. The experimental data verifies the effectiveness of the GHMST in fault diagnosis of mechanical system.
Important Date
  • Conference Date

    Nov 01

    2022

    to

    Nov 03

    2022

  • Oct 30 2022

    Draft paper submission deadline

  • Nov 09 2022

    Registration deadline

Sponsored By
Qingdao University of Technology