Short-time Fourier transform (STFT)-based methods are widely applied in industrial areas. However, these methods are inadequate to process non-stationary signals under variable operating conditions. An improved general linear chirplet transform… Click to show full abstract
Short-time Fourier transform (STFT)-based methods are widely applied in industrial areas. However, these methods are inadequate to process non-stationary signals under variable operating conditions. An improved general linear chirplet transform method is developed by iteratively upgrading the instantaneous frequency (IF) and introducing a synchrosqueezing operator simultaneously. Initially, an iterative upgrading strategy is adopted to improve the estimation accuracy of the IF curves. Then, a synchrosqueezing operator is employed to enhance the concentration of the time-frequency representation under variable operating conditions. Finally, experiments that utilize simulated data are conducted to verify the effectiveness. Experimental results show that the enhanced time-frequency analysis (TFA) method can sharpen IF curves and enhance the time-frequency readability compared with other advanced TFA methods. Moreover, the feature extraction ability of the present method is superior to other commonly used methods.
               
Click one of the above tabs to view related content.