Variable short-time Fourier transform for vibration signals with transients

This paper presents a fast adaptive time-frequency method for analyzing stationary and nonstationary vibration signals with transients. The method is developed based on instantaneous frequency (IF) – variations in the time domain. The variable window length is determined by estimating the local IF in every window slice over time. The proposed method is tested using simulation signals and experimental vibration data. The results show that the proposed method can successfully retrieve transient signals at a 3 dB signal-to-noise ratio, and improve stationary and nonstationary signal resolution in time and frequency domains. The proposed scheme offers better resolution compared to the standard short-time Fourier transform (STFT), and the computing cost is only slightly greater than STFT scheme.

[1]  Bruno Torrésani,et al.  Characterization of signals by the ridges of their wavelet transforms , 1997, IEEE Trans. Signal Process..

[2]  June-Yule Lee Adaptive Choice of Trimming Proportions for Location Estimation of the Mean , 2004 .

[3]  Jin Jiang,et al.  Time-frequency feature representation using energy concentration: An overview of recent advances , 2009, Digit. Signal Process..

[4]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[5]  Richard G. Baraniuk,et al.  Pseudo affine Wigner distributions: definition and kernel formulation , 1998, IEEE Trans. Signal Process..

[6]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

[7]  Richard Kronland-Martinet,et al.  Asymptotic wavelet and Gabor analysis: Extraction of instantaneous frequencies , 1992, IEEE Trans. Inf. Theory.

[8]  Paul R. White,et al.  THE ANALYSIS OF NON-STATIONARY SIGNALS USING TIME-FREQUENCY METHODS , 1996 .

[9]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[10]  Douglas L. Jones,et al.  An adaptive optimal-kernel time-frequency representation , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[11]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. II. A/lgorithms and applications , 1992, Proc. IEEE.

[12]  Yu Huang,et al.  Time-Frequency Representation Based on an Adaptive Short-Time Fourier Transform , 2010, IEEE Transactions on Signal Processing.

[13]  Les E. Atlas,et al.  Optimizing time-frequency kernels for classification , 2001, IEEE Trans. Signal Process..

[14]  Douglas L. Jones,et al.  A signal-dependent time-frequency representation: optimal kernel design , 1993, IEEE Trans. Signal Process..