Methods to isolate retrograde and prograde Rayleigh-wave signals

2019 ◽  
Vol 219 (2) ◽  
pp. 975-994 ◽  
Author(s):  
Gabriel Gribler ◽  
T Dylan Mikesell
Keyword(s):  
Rayleigh Wave ◽  
Time Domain ◽  
Fundamental Mode ◽  
Poisson Ratio ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Low Frequencies ◽  
Retrograde Motion ◽  
Mode Identification ◽  
Time Frequency

SUMMARY Estimating shear wave velocity with depth from Rayleigh-wave dispersion data is limited by the accuracy of fundamental and higher mode identification and characterization. In many cases, the fundamental mode signal propagates exclusively in retrograde motion, while higher modes propagate in prograde motion. It has previously been shown that differences in particle motion can be identified with multicomponent recordings and used to separate prograde from retrograde signals. Here we explore the domain of existence of prograde motion of the fundamental mode, arising from a combination of two conditions: (1) a shallow, high-impedance contrast and (2) a high Poisson ratio material. We present solutions to isolate fundamental and higher mode signals using multicomponent recordings. Previously, a time-domain polarity mute was used with limited success due to the overlap in the time domain of fundamental and higher mode signals at low frequencies. We present several new approaches to overcome this low-frequency obstacle, all of which utilize the different particle motions of retrograde and prograde signals. First, the Hilbert transform is used to phase shift one component by 90° prior to summation or subtraction of the other component. This enhances either retrograde or prograde motion and can increase the mode amplitude. Secondly, we present a new time–frequency domain polarity mute to separate retrograde and prograde signals. We demonstrate these methods with synthetic and field data to highlight the improvements to dispersion images and the resulting dispersion curve extraction.

scholarly journals A SFTD Algorithm for Optimizing the Performance of the Readout Strategy of Residence Time Difference Fluxgate

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3985 ◽  
Author(s):  
Siyu Chen ◽  
Yanzhang Wang ◽  
Jun Lin
Keyword(s):  
Residence Time ◽  
Time Domain ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Transformation Method ◽  
Time Difference ◽  
Single Frequency ◽  
Time Frequency ◽  
Frequency Magnetic Field ◽  
The Time Domain

Residence time difference (RTD) fluxgate sensor is a potential device to measure the DC or low-frequency magnetic field in the time domain. Nevertheless, jitter noise and magnetic noise severely affect the detection result. A novel post-processing algorithm for jitter noise reduction of RTD fluxgate output strategy based on the single-frequency time difference (SFTD) method is proposed in this study to boost the performance of the RTD system. This algorithm extracts the signal that has a fixed frequency and preserves its time-domain information via a time–frequency transformation method. Thereby, the single-frequency signal without jitter noise, which still contains the ambient field information in its time difference, is yielded. Consequently, compared with the traditional comparator RTD method (CRTD), the stability of the RTD estimation (in other words, the signal-to-noise ratio of residence time difference) has been significantly boosted with sensitivity of 4.3 μs/nT. Furthermore, the experimental results reveal that the RTD fluxgate is comparable to harmonic fluxgate sensors, in terms of noise floor.

Time Frequency Domain Analysis of the Dispersion of Guided Wave Modes

2004 ◽  
Author(s):  
Youn-Ho Cho ◽  
Yong-Kwon Kim ◽  
Ik-Keun Park
Keyword(s):  
Wavelet Transform ◽  
Group Velocity ◽  
Frequency Analysis ◽  
Time Domain ◽  
Excitation Frequency ◽  
Guided Wave ◽  
Time Frequency Analysis ◽  
Mode Identification ◽  
Time Frequency ◽  
Wave Modes

One of unique characteristics of guided waves is a dispersive behavior that guided wave velocity changes with an excitation frequency and mode. In practical applications of guided wave techniques, it is very important to identify propagating modes in a time-domain waveform for determination of defect location and size. Mode identification can be done by measurement of group velocity in a time-domain waveform. Thus, it is preferred to generate a single or less dispersive mode. But, in many cases, it is difficult to distinguish a mode clearly in a time-domain waveform because of superposition of multi modes and mode conversion phenomena. Time-frequency analysis is used as efficient methods to identify modes by presenting wave energy distribution in a time-frequency. In this study, experimental guided wave mode identification is carried out in a steel plate using time-frequency analysis methods such as wavelet transform. The results are compared with theoretically calculated group velocity dispersion curves. The results are in good agreement with analytical predictions and show the effectiveness of using the wavelet transform method to identify and measure the amplitudes of individual guided wave modes.

Combination of Active and Passive Seismic Analyses for Embankment Characterization

2015 ◽  
Vol 771 ◽  
pp. 179-182 ◽  
Author(s):  
Yekti Widyaningrum ◽  
Sungkono ◽  
Alwi Husein ◽  
Bagus Jaya Santosa ◽  
Ayi S. Bahri
Keyword(s):  
Rayleigh Wave ◽  
High Frequency ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Standard Penetration Test ◽  
Near Surface ◽  
Combining Data ◽  
Passive Seismic ◽  
Estimate Dispersion ◽  
Rayleigh Wave Dispersion

Rayleigh wave dispersion is intensively used to determine near surface of shear wave velocity (Vs). The method has been known as non-invasive techniques which is costly effective and efficient to characterize subsurface. Acquisition of the Rayleigh wave can be approached in two ways, i.e. passive and active. Passive seismic is accurate to estimate dispersion curve in low frequency, although it is not accurate for high frequency. While active seismic is vice versa of passive seismic. The high frequency of Rayleigh wave dispersion reflects to near surface and vice versa. Therefore, we used the combination of both passive and active seismic method to overcome the limitations of each method. The Vs which is resulted by inversion of the combining data gives accurate model if compared to log and standard penetration test (N-SPT) data. Further, the approach has been used to characterize LUSI (Lumpur Sidoarjo) embankments. The result shows that embankment material (0-12 m) has higher Vs than that lower embankment material.

ON THE USE OF THE REASSIGNED WAVELET TRANSFORM FOR MODE IDENTIFICATION

2004 ◽  
Vol 12 (02) ◽  
pp. 175-196 ◽  
Author(s):  
MICHAEL I. TAROUDAKIS ◽  
GEORGE TZAGKARAKIS
Keyword(s):  
Wavelet Transform ◽  
Shallow Water ◽  
Underwater Acoustics ◽  
Low Frequency ◽  
Energy Concentration ◽  
Propagation Mode ◽  
Mode Identification ◽  
Time Frequency ◽  
Frequency Representation ◽  
Calculation Point

This paper is concerned with the use of the reassigned wavelet transform for mode identification in shallow water acoustic propagation. Mode identification is important for inverse procedures in underwater acoustics. An efficient way to recognize the modal structure of the acoustic field when a single hydrophone is available is to refer to the time frequency analysis of the recorded signal using wavelet transform. However, the standard wavelet transform in some cases may result in an obscure representation of the dispersion curves. Thus, a reassigned process is proposed which brings important improvements in the time frequency representation of the signal. This is achieved by moving the calculation point of the scalogram in the center of gravity of the energy concentration, associated with each one of the propagating modes. This argument is supported by two illustrative examples corresponding to propagation of low frequency tomographic signals, in shallow water.

Study on the Dispersion Curves of Rayleigh Wave in Foundation of Obstacles

2011 ◽  
Vol 90-93 ◽  
pp. 2193-2199
Author(s):  
Fang Ding He ◽  
Guang Jun Guo ◽  
Zhi Gang Dou ◽  
Yang Yang
Keyword(s):  
Finite Element ◽  
Rayleigh Wave ◽  
Half Space ◽  
Time Domain ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Displacement Curve ◽  
Rayleigh Wave Dispersion ◽  
Water Drain

It is difficult to accurately identify dispersion curves of Rayleigh wave for the foundation with obstacles. Displacement curve of time-domain of half-space foundation have been obtained with the finite element in the paper. Then time-domain curve have been transformed Rayleigh wave dispersion curves. Rayleigh wave dispersion curves have been analysed in half-space foundation with water drain pipes. The results show that, there are reflection waves at the receiving signals in front of the obstacles, there are no reflection waves behind the obstacles basically. The location and spacing of the sensor have a greater impact on the results. The results provide the reference for the recognition of dispersion curves and disposition patterns of the sensors.

Localization of Lamb Wave Scattering Source Based on Time-Frequency Analysis

2013 ◽  
Vol 281 ◽  
pp. 276-281
Author(s):  
Ding Ma ◽  
Li Hua Shi ◽  
Shang Chen Fu ◽  
Hong Fu Cao
Keyword(s):  
Lamb Wave ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Frequency Component ◽  
Localization Method ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Frequency Components ◽  
Scattering Signal ◽  
Frequency Curves

Considering the influence of Lamb wave dispersion on the precision of damage detection, a new detection method of scattering source based on time-frequency curves and ellipse localization method is proposed. Empirical mode decomposition(EMD) is used to decompose the scattering signal into finite narrowband signals, and a modified continuous wavelet transform(CWT) is further used to get the time-frequency distribution(TFD) of the detected signal, and the arriving time of different frequency component is estimated based on TFD. A series of location results can be obtained from different frequency components using ellipse localization method. The damage position can finally be estimated by synthesizing localization results at different frequencies. Experiments on aluminum plate are conducted to demonstrate the efficiency of the proposed method. EMD-CWT analysis can get precise time-frequency curves in highly dispersive low frequency band of A0 mode. The damage location results is more accurate and the influence from occasional factors can be suppressed by using the synthesized method.

scholarly journals Unified cochlear model for low- and high-frequency mammalian hearing

2019 ◽  
Vol 116 (28) ◽  
pp. 13983-13988 ◽  
Author(s):  
Aritra Sasmal ◽  
Karl Grosh
Keyword(s):  
Spatial Variation ◽  
Outer Hair Cell ◽  
Low Frequency ◽  
Auditory Nerve Fiber ◽  
Physiological Basis ◽  
Low Frequencies ◽  
Tuning Curves ◽  
Time Frequency ◽  
The Difference ◽  
Mechanical Tuning

The spatial variations of the intricate cytoarchitecture, fluid scalae, and mechano-electric transduction in the mammalian cochlea have long been postulated to provide the organ with the ability to perform a real-time, time-frequency processing of sound. However, the precise manner by which this tripartite coupling enables the exquisite cochlear filtering has yet to be articulated in a base-to-apex mathematical model. Moreover, while sound-evoked tuning curves derived from mechanical gains are excellent surrogates for auditory nerve fiber thresholds at the base of the cochlea, this correlation fails at the apex. The key factors influencing the divergence of both mechanical and neural tuning at the apex, as well as the spatial variation of mechanical tuning, are incompletely understood. We develop a model that shows that the mechanical effects arising from the combination of the taper of the cochlear scalae and the spatial variation of the cytoarchitecture of the cochlea provide robust mechanisms that modulate the outer hair cell-mediated active response and provide the basis for the transition of the mechanical gain spectra along the cochlear spiral. Further, the model predicts that the neural tuning at the base is primarily governed by the mechanical filtering of the cochlear partition. At the apex, microscale fluid dynamics and nanoscale channel dynamics must also be invoked to describe the threshold neural tuning for low frequencies. Overall, the model delineates a physiological basis for the difference between basal and apical gain seen in experiments and provides a coherent description of high- and low-frequency cochlear tuning.

scholarly journals Transformation Algorithm of Dielectric Response in Time-Frequency Domain

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ji Liu ◽  
Daning Zhang ◽  
Xinlao Wei ◽  
Hamid Reza Karimi
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Dielectric Response ◽  
Low Frequency ◽  
Dissipation Factor ◽  
Depolarization Current ◽  
Ultralow Frequency ◽  
Time Frequency ◽  
Transformation Algorithm ◽  
The Time Domain

A transformation algorithm of dielectric response from time domain to frequency domain is presented. In order to shorten measuring time of low or ultralow frequency dielectric response characteristics, the transformation algorithm is used in this paper to transform the time domain relaxation current to frequency domain current for calculating the low frequency dielectric dissipation factor. In addition, it is shown from comparing the calculation results with actual test data that there is a coincidence for both results over a wide range of low frequencies. Meanwhile, the time domain test data of depolarization currents in dry and moist pressboards are converted into frequency domain results on the basis of the transformation. The frequency domain curves of complex capacitance and dielectric dissipation factor at the low frequency range are obtained. Test results of polarization and depolarization current (PDC) in pressboards are also given at the different voltage and polarization time. It is demonstrated from the experimental results that polarization and depolarization current are affected significantly by moisture contents of the test pressboards, and the transformation algorithm is effective in ultralow frequency of 10−3 Hz. Data analysis and interpretation of the test results conclude that analysis of time-frequency domain dielectric response can be used for assessing insulation system in power transformer.

Lamb Wave Instantaneous Phase Based Method for Quantitative Level of Delamination Damage in Composite Structures

2012 ◽  
Author(s):  
Dulip Samaratunga ◽  
Ruisheng Wang ◽  
Ratneshwar Jha
Keyword(s):  
Finite Element ◽  
Lamb Wave ◽  
Composite Structures ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Finite Element Simulations ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Instantaneous Phase ◽  
Quantitative Level

In this study, we investigate the interactions of Lamb wave A0 mode with different sizes of delaminations in composites using finite element code Abaqus®. According to Lamb wave dispersion curves, the group velocity of A0 mode increases rapidly as the frequency-thickness increases in the relatively low frequency region. In the delamination region, the frequency-thickness product decreases compared to the healthy laminate since the damage causes ply separation at the lamina interface. In the current study this observation is investigated in detail using finite element simulations. The resulting phase delay is analyzed by Empirical Mode Decomposition (EMD) and instantaneous phase approach. Finite element simulations are performed using Abaqus® and signal processing is performed in joint time-frequency domain using Hilbert-Huang Transform (HHT) method. The unwrapped instantaneous phase difference is correlated with the extent of delamination (quantitative level of damage).

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