Slider Vibration Analysis at Contact Using Time-Frequency Analysis and Wavelet Transforms

2000 ◽  
Vol 123 (3) ◽  
pp. 548-554 ◽  
Author(s):  
Bernhard Knigge ◽  
Frank E. Talke
Keyword(s):  
Frequency Analysis ◽  
Wavelet Transforms ◽  
Contact Dynamics ◽  
Frequency Resolution ◽  
High Time Resolution ◽  
Time Frequency Analysis ◽  
Hard Drives ◽  
Disk Interface ◽  
Time Frequency ◽  
Transient Contact

Time-frequency analysis and wavelet transforms are employed to investigate transient contact dynamics at the head/disk interface of computer hard drives. Wavelet transforms are used to resolve multiple short consecutive contacts at high time resolution at high frequencies. The reassignment method is applied to the time-frequency distribution to enhance the time-frequency resolution, thereby allowing to resolve air-bearing and slider body frequencies simultaneously. The results indicate that strong impacts between slider and disk can lead to excitations of slider body and suspension vibrations. Finite element modal analysis of nano and pico glide sliders is found to be in good agreement with experimentally measured frequencies.

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

scholarly journals Time-Frequency Analysis Based on Minimum-Norm Spectral Estimation to Detect Induction Motor Faults

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4102
Author(s):  
Tomas A. Garcia-Calva ◽  
Daniel Morinigo-Sotelo ◽  
Oscar Duque-Perez ◽  
Arturo Garcia-Perez ◽  
Rene de J. Romero-Troncoso
Keyword(s):  
Fault Detection ◽  
Frequency Analysis ◽  
Induction Motors ◽  
Spectral Estimation ◽  
Diagnostic Techniques ◽  
Frequency Resolution ◽  
Minimum Norm ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Stationary Conditions

In this work, a new time-frequency tool based on minimum-norm spectral estimation is introduced for multiple fault detection in induction motors. Several diagnostic techniques are available to identify certain faults in induction machines; however, they generally give acceptable results only for machines operating under stationary conditions. Induction motors rarely operate under stationary conditions as they are constantly affected by load oscillations, speed waves, unbalanced voltages, and other external conditions. To overcome this issue, different time-frequency analysis techniques have been proposed for fault detection in induction motors under non-stationary regimes. However, most of them have low-resolution, low-accuracy or both. The proposed method employs the minimum-norm spectral estimation to provide high frequency resolution and accuracy in the time-frequency domain. This technique exploits the advantages of non-stationary conditions, where mechanical and electrical stresses in the machine are higher than in stationary conditions, improving the detectability of fault components. Numerical simulation and experimental results are provided to validate the effectiveness of the method in starting current analysis of induction motors.

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 Bridge Dynamic Cable-Tension Estimation with Interferometric Radar and APES-Based Time-Frequency Analysis

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 501
Author(s):  
Jian Wang ◽  
Xiang Wang ◽  
Chongyi Fan ◽  
Yueli Li ◽  
Xiaotao Huang
Keyword(s):  
Frequency Analysis ◽  
Field Experiments ◽  
Displacement Vector ◽  
Frequency Resolution ◽  
Cable Tension ◽  
Time Frequency Analysis ◽  
Vibration Equation ◽  
Time Frequency ◽  
String Vibration ◽  
Analysis Technique

Dynamic cable-tension is an important bridge-health indicator. However, it is difficult to be measured precisely and efficiently. A remote bridge dynamic cable-tension measurement method is proposed. It uses an interferometric radar sensor, a time-frequency analysis technique, and a tension estimation approach based on a string-vibration-equation. One radar can measure the displacements of multiple cables aligned on one side of a bridge, at the same time. By solving the string vibration equation, each cable-tension is calculated from its fundamental frequency, which is obtained by time-frequency analyzing a short section of the cable’s whole displacement vector in an overlapped-piecewise manner. An adaptive amplitude and phase estimation (APES) algorithm is used to solve the frequency resolution deterioration problem due to the short duration. Simulations and field experiments with a K band interferometric radar validate that the proposed method is superior to traditional cable-tension measurements in terms of precision, robustness, and efficiency. The proposed method is of great application value in measuring and monitoring large cable-stayed bridges and cable-suspended bridges.

scholarly journals An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2814
Author(s):  
Cao Zeng ◽  
Mengyi Qin ◽  
Dong Li ◽  
Hongqing Liu ◽  
Yi Chai
Keyword(s):  
Parameter Estimation ◽  
Frequency Analysis ◽  
Frequency Resolution ◽  
Cubic Phase ◽  
Noise Resistance ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Coherent Integration ◽  
Isar Imaging ◽  
The Cross

The inverse synthetic aperture radar (ISAR) imaging for targets with complex motions has always been a challenging task due to the time-varying Doppler parameter, especially at the low signal-to-noise ratio (SNR) condition. In this paper, an efficient ISAR imaging algorithm for maneuvering targets based on a noise-resistance bilinear coherent integration is developed without the parameter estimation. First, the received signals of the ISAR in a range bin are modelled as a multicomponent quadratic frequency-modulated (QFM) signal after the translational motion compensation. Second, a novel quasi-time-frequency representation noise-resistance bilinear Radon-cubic phase function (CPF)-Fourier transform (RCFT) is proposed, which is based on the coherent integration of the energy of auto-terms along the slope line trajectory. In doing so, the RCFT also effectively suppresses the cross-terms and spurious peaks interference at no expense of the time-frequency resolution loss. Third, the cross-range positions of target’s scatters in ISAR image are obtained via a simple maximization projection from the RCFT result to the Doppler centroid axis, and the final high-resolution ISAR image is thus produced by regrouping all the range-Doppler frequency centroids. Compared with the existing time-frequency analysis-based and parameter estimation-based ISAR imaging algorithms, the proposed method presents the following features: (1) Better cross-term interference suppression at no time-frequency resolution loss; (2) computationally efficient without estimating the parameters of each scatters; (3) higher signal processing gain because of 2-D coherent integration realization and its bilinear function feature. The simulation results are provided to demonstrate the performance of the proposed method.

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