Time-Frequency Analysis of Shock and Vibration Measurements Using Wavelet Transforms

2014 ◽  
Vol 2 (1) ◽  
pp. 60-69
Author(s):  
Divya Choudhary ◽  
◽  
Siripong Malasri ◽  
Mallory Harvey ◽  
Amanda Smith
Keyword(s):  
Frequency Analysis ◽  
Wavelet Transforms ◽  
Vibration Measurements ◽  
Time Frequency Analysis ◽  
Time Frequency

Time-frequency analysis of electroencephalogram series. II. Gabor and wavelet transforms

1996 ◽  
Vol 54 (6) ◽  
pp. 6661-6672 ◽  
Author(s):  
S. Blanco ◽  
C. E. D'Attellis ◽  
S. I. Isaacson ◽  
O. A. Rosso ◽  
R. O. Sirne
Keyword(s):  
Frequency Analysis ◽  
Wavelet Transforms ◽  
Time Frequency Analysis ◽  
Time Frequency

Application of bi-Gaussian S-transform in high-resolution seismic time-frequency analysis

2017 ◽  
Vol 5 (1) ◽  
pp. SC1-SC7 ◽  
Author(s):  
Zixiang Cheng ◽  
Wei Chen ◽  
Yangkang Chen ◽  
Ying Liu ◽  
Wei Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Frequency Analysis ◽  
Time Resolution ◽  
Wavelet Transforms ◽  
Superior Performance ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Gaussian Window ◽  
Hydrocarbon Reservoir ◽  
S Transform

The S-transform is one of the most widely used methods of time-frequency analysis. It combines the respective advantages of the short-time Fourier transform and wavelet transforms with scale-dependent resolution using Gaussian windows, scaled inversely with frequency. One of the problems with the traditional symmetric Gaussian window is the degradation of time resolution in the time-frequency spectrum due to the long front taper. We have studied the performance of an improved S-transform with an asymmetric bi-Gaussian window. The asymmetric bi-Gaussian window can obtain an increased time resolution in the front direction. The increased time resolution can make event picking high resolution, which will facilitate an improved time-frequency characterization for oil and gas trap prediction. We have applied the slightly modified bi-Gaussian S-transform to a synthetic trace, a 2D seismic section, and a 3D seismic cube to indicate the superior performance of the bi-Gaussian S-transform in analyzing nonstationary signal components, hydrocarbon reservoir predictions, and paleochannels delineations with an obviously higher resolution.

Optimal Windows for the Time-Frequency Analysis of Arbitrary Swept Frequency Signals

1995 ◽  
Author(s):  
James A. Mooney ◽  
Andres Soom
Keyword(s):  
Frequency Analysis ◽  
Wavelet Transforms ◽  
Fourier Transforms ◽  
Rate Of Change ◽  
Effective Bandwidth ◽  
Instantaneous Rate ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Analysis Window ◽  
Constant Bandwidth

Abstract In noise and vibration analysis, as well as in many other engineering applications, it may be necessary to extract or analyze signals with time-varying frequency components. Examples include start-up and shut-down of rotating machinery, transient structural vibrations, vehicle passing noise, and speech analysis. Both Short-Time Fourier Transforms (STFT), representing a set of non-causal filters of constant bandwidth, and Wavelet Transforms, representing a set of non-causal filters of constant Q or constant percent bandwidth, have been used for such Joint Time Frequency Analysis (JTFA). In the present work, an arbitrary swept frequency signal is approximated locally, in time, by a linearized frequency sweep. We show that an optimal time window can be identified which, at a given frequency, is inversely proportional to the square root of the instantaneous rate of change of frequency. We find that the constant bandwidth of the STFT and the constant-Q of the Wavelet transform represent extreme cases which are each optimal for certain types of signals. In between the two extremes there lies a continuous range of variation of the effective bandwidth with frequency. Many important types of signals require analysis window variation in this range between STFT and Wavelet analysis. The paper concludes with some simple rules for optimizing the variation of the analysis window with frequency for various types of signals.

scholarly journals Determining Time Variation of Cable Tension Forces in Suspended Bridges Using Time-Frequency Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Gannon Stromquist-LeVoir ◽  
Kevin F. McMullen ◽  
Arash E. Zaghi ◽  
Richard Christenson
Keyword(s):  
Frequency Analysis ◽  
Ambient Vibration ◽  
Vibration Measurements ◽  
Cable Tension ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Tensile Forces ◽  
Motion Studies ◽  
Ambient Vibration Measurements ◽  
Cable Forces

A feasibility study was conducted to develop a novel method to determine the temporal changes of tensile forces in bridge suspender cables using time-frequency analysis of ambient vibration measurements. An analytical model of the suspender cables was developed to evaluate the power spectral density (PSD) function of a cable with consideration of cable flexural stiffness. Discrete-time, short-time Fourier transform (STFT) was utilized to analyze the recorded acceleration histories in both time and frequency domains. A mathematical convolution of the analytical PSD function and time-frequency data was completed to evaluate changes in cable tension force over time. The method was implemented using acceleration measurements collected from an in-service steel arch bridge with a suspended deck to calculate the temporal variation in cable forces from the vibration measurements. The observations served as proof of concept that the proposed method may be used for cable fatigue life calculations and bridge weigh-in-motion studies.

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