Open AccessJournal Article
Synchroextracting Transform
Gang Yu,Mingjin Yu,Chuanyan Xu +2 more
TLDR
The main idea of SET is to only retain the TF information of STFT results most related to time-varying features of the signal and to remove most smeared TF energy, such that the energy concentration of the novel TF representation can be enhanced greatly.Abstract:
In this paper, we introduce a new time-frequency (TF) analysis (TFA) method to study the trend and instantaneous frequency (IF) of nonlinear and nonstationary data. Our proposed method is termed the synchroextracting transform (SET), which belongs to a postprocessing procedure of the short-time Fourier transform (STFT). Compared with classical TFA methods, the proposed method can generate a more energy concentrated TF representation and allow for signal reconstruction. The proposed SET method is inspired by the recently proposed synchrosqueezing transform (SST) and the theory of the ideal TFA. To analyze a signal, it is important to obtain the time-varying information, such as the IF and instantaneous amplitude. The SST is to squeeze all TF coefficients into the IF trajectory. Differ from the squeezing manner of SST, the main idea of SET is to only retain the TF information of STFT results most related to time-varying features of the signal and to remove most smeared TF energy, such that the energy concentration of the novel TF representation can be enhanced greatly. Numerical and real-world signals are employed to validate the effectiveness of the SET method.read more
Citations
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Fractional Stockwell transform: Theory and applications
Deyun Wei,Yijie Zhang +1 more
TL;DR: In this paper, the authors proposed the fractional stockwell transform (FRST) based on the Stockwell transform and fractional Fourier transform to address the problem of signal analysis in the time-frequency domain.
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Enhanced Time-Frequency Representation and Mode Decomposition
TL;DR: In this paper, an enhanced TFR and mode decomposition (ETFR-MD) method was proposed to represent and decompose multi-mode signals with closely-spaced or spectrally-overlapped instantaneous frequencies.
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Multi-synchrosqueezing S-transform for fault diagnosis in rolling bearings
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Crack propagation monitoring of rotor blades using synchroextracting transform
TL;DR: In this article, the authors proposed a method to detect the cracks of rotor blades by the natural frequency shift of the cracked blades using a synchroextracting transform with the advantage of high time-frequency resolution.
Journal ArticleDOI
Matching Synchroextracting Transform for Mechanical Fault Diagnosis Under Variable-Speed Conditions
TL;DR: In this article , the synchroextracting transform was extended to a prior instantaneous frequency (IF) based method, named Matching Synchro Extracting Transform (MSET).
References
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The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
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Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool
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Journal ArticleDOI
Improving the readability of time-frequency and time-scale representations by the reassignment method
François Auger,Patrick Flandrin +1 more
TL;DR: The reassignment method, first applied by Kodera, Gendrin, and de Villedary (1976) to the spectrogram, is generalized to any bilinear time-frequency or time-scale distribution.
Journal ArticleDOI
Joint time-frequency analysis
Shie Qian,Dapang Chen +1 more
TL;DR: This article introduces the so-called model-based (or parametric) time-frequency analysis method, and introduces the basic concepts and well-tested algorithms for joint time- frequencies analysis.
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Time-Frequency Reassignment and Synchrosqueezing: An Overview
François Auger,Patrick Flandrin,Yu-Ting Lin,Stephen McLaughlin,Sylvain Meignen,Thomas Oberlin,Hau-Tieng Wu +6 more
TL;DR: This article provides a general overview of time-frequency (T-F) reassignment and synchrosqueezing techniques applied to multicomponent signals, covering the theoretical background and applications.
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