Abstract detail

21 / 2021-03-16 21:19:52
Generalized Horizontal Multi-synchrosqueezing Transform
Nonstationary signal; Time-frequency analysis (TFA); Synchrosqueezing transform (SST); Fault diagnosis
Special Sessions > Nonstationary signal processing algorithms and applications
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.

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Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

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