Litcius/Paper detail

Time‐frequency synchroextracting transform

Ran Zhang, Xingxing Liu, Yongjun Zheng, Haotun Lv, Baosheng Li, Shenghui Yang, Yu Tan

2021IET Signal Processing22 citationsDOIOpen Access PDF

Abstract

Abstract The study proposes a novel time‐frequency analysis technique, titled time‐frequency synchroextracting transform which enhances the accuracy of synchroextracting transform. The synchroextracting transform is a powerful postprocessing method that sharpens the energy distribution of spectrogram. However, its limitation is the sole use of time or frequency factors that cannot accurately portray signals containing both ‘slow‐varying’ and ‘fast‐changing’ components. The proposed method applies the synchroextracting procedure in both time and frequency dimensions to improve the energy concentration. A fast Fourier transform‐‐based algorithm is also provided for efficient implementation. The proposed method is validated via numerical and empirical data. Compared with advanced methods including synchrosqueezing transform and synchroextracting transform, the proposed method is suitable to analyse wider range of signals and has better noise robustness than the original synchroextracting transform.

Topics & Concepts

Time–frequency analysisS transformRobustness (evolution)Computer scienceSpectrogramShort-time Fourier transformAlgorithmFourier transformEnergy (signal processing)Range (aeronautics)Fractional Fourier transformHarmonic wavelet transformConstant Q transformHilbert–Huang transformSpeech recognitionArtificial intelligenceMathematicsWavelet transformComputer visionFourier analysisStatisticsDiscrete wavelet transformFilter (signal processing)EngineeringGeneWaveletAerospace engineeringChemistryMathematical analysisBiochemistryMachine Fault Diagnosis TechniquesAdvanced Electrical Measurement TechniquesPower Transformer Diagnostics and Insulation