A high-resolution time-frequency analysis technique based on bi-directional squeezing and its application in fault diagnosis of rotating machinery
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View abstract on PubMed
Summary
This summary is machine-generated.A new time-frequency squeezing transform accurately analyzes nonstationary industrial signals. This method enhances the simultaneous characterization of instantaneous frequency and group delay for better signal analysis.
Area Of Science
- Industrial Engineering
- Signal Processing
- Applied Mathematics
Background
- Nonstationary signals are prevalent in industrial engineering.
- Accurate time-frequency (TF) analysis is crucial for understanding these signals.
- Existing methods like synchrosqueezing transform struggle to simultaneously characterize instantaneous frequency (IF) and group delay (GD).
Purpose Of The Study
- To introduce a novel time-frequency squeezing transform (TFST) method.
- To overcome the limitations of existing TF analysis tools in simultaneously characterizing IF and GD.
- To provide a high-resolution TF analysis for nonstationary signals.
Main Methods
- Utilizes the short-time Fourier transform (STFT) to compute the time-frequency representation (TFR).
- Employs a chirp rate estimator to divide the TFR into two components.
- Applies frequency squeezing to IF and time squeezing to GD, then combines the results.
Main Results
- The proposed TFST method accurately characterizes both IF and GD simultaneously.
- Achieves high-resolution time-frequency analysis.
- Demonstrated effectiveness on both numerical and experimental signals.
Conclusions
- The novel time-frequency squeezing transform offers a superior approach for analyzing nonstationary signals in industrial engineering.
- This method improves the simultaneous estimation of key TF features (IF and GD).
- TFST provides a valuable tool for advancing industrial engineering applications requiring precise signal analysis.
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