scholarly journals Group Velocity Measurement of Surface Waves by the Wavelet Transform.

1997 ◽  
Vol 45 (5) ◽  
pp. 313-329 ◽  
Author(s):  
Takeshi Yamada ◽  
Kiyoshi Yomogida
1999 ◽  
Vol 66 (2) ◽  
pp. 507-513 ◽  
Author(s):  
T.-T. Wu ◽  
Y.-Y. Chen

This paper presents the results on the utilization of a wavelet transform to study the dispersion of laser-generated surface waves in an epoxy-bonded copper-aluminum layered specimen with and without unbond areas. Laser ultrasonic experiments based on the point-source/point-receiver (PS/PR) technique were undertaken to measure surface wave signals in a layered specimen. The wavelet transform with a Morlet wavelet function was adopted to analyze the group velocity dispersion of the surface wave signals. A novel hybrid formula for group velocity dispersion is proposed for measurements across unbond regions. Results and data obtained are in good agreement with calculated and experimental dispersion curves. The general behavior of the group velocity dispersion for different measurement, configurations can be utilized to differentiate the unbond regions in a layered structure.


Geophysics ◽  
2003 ◽  
Vol 68 (2) ◽  
pp. 677-684 ◽  
Author(s):  
Helle A. Pedersen ◽  
Jérôme I. Mars ◽  
Pierre‐Olivier Amblard

Surface waves are increasingly used for shallow seismic surveys—in particular, in acoustic logging, environmental, and engineering applications. These waves are dispersive, and their dispersion curves are used to obtain shear velocity profiles with depth. The main obstacle to their more widespread use is the complexity of the associated data processing and interpretation of the results. Our objective is to show that energy reassignment in the time–frequency domain helps improve the precision of group velocity measurements of surface waves. To show this, full‐waveform seismograms with added white noise for a shallow flat‐layered earth model are analyzed by classic and reassigned multiple filter analysis (MFA). Classic MFA gives the expected smeared image of the group velocity dispersion curve, while the reassigned curve gives a very well‐constrained, narrow dispersion curve. Systematic errors from spectral fall‐off are largely corrected by the reassignment procedure. The subsequent inversion of the dispersion curve to obtain the shear‐wave velocity with depth is carried out through a procedure combining linearized inversion with a nonlinear Monte Carlo inversion. The diminished uncertainty obtained after reassignment introduces significantly better constraints on the earth model than by inverting the output of classic MFA. The reassignment is finally carried out on data from a shallow seismic survey in northern Belgium, with the aim of determining the shear‐wave velocities for seismic risk assessment. The reassignment is very stable in this case as well. The use of reassignment can make dispersion measurements highly automated, thereby facilitating the use of surface waves for shallow surveys.


2020 ◽  
Vol 91 (4) ◽  
pp. 2234-2246
Author(s):  
Hang Li ◽  
Jianqiao Xu ◽  
Xiaodong Chen ◽  
Heping Sun ◽  
Miaomiao Zhang ◽  
...  

Abstract Inversion of internal structure of the Earth using surface waves and free oscillations is a hot topic in seismological research nowadays. With the ambient noise data on seismically quiet days sourced from the gravity tidal observations of seven global distributed superconducting gravimeters (SGs) and the seismic observations for validation from three collocated STS-1 seismometers, long-period surface waves and background free oscillations are successfully extracted by the phase autocorrelation (PAC) method, respectively. Group-velocity dispersion curves at the frequency band of 2–7.5 mHz are extracted and compared with the theoretical values calculated with the preliminary reference Earth model. The comparison shows that the best observed values differ about ±2% from the corresponding theoretical results, and the extracted group velocities of the best SG are consistent with the result of the collocated STS-1 seismometer. The results indicate that reliable group-velocity dispersion curves can be measured with the ambient noise data from SGs. Furthermore, the fundamental frequency spherical free oscillations of 2–7 mHz are also clearly extracted using the same ambient noise data. The results in this study show that the SG, besides the seismometer, is proved to be another kind of instrument that can be used to observe long-period surface waves and free oscillations on seismically quiet days with a high degree of precision using the PAC method. It is worth mentioning that the PAC method is first and successfully introduced to analyze SG observations in our study.


1994 ◽  
Vol 37 (3) ◽  
Author(s):  
R. G. North ◽  
C. R. D. Woodgold

An algorithm for the automatic detection and association of surface waves has been developed and tested over an 18 month interval on broad band data from the Yellowknife array (YKA). The detection algorithm uses a conventional STA/LTA scheme on data that have been narrow band filtered at 20 s periods and a test is then applied to identify dispersion. An average of 9 surface waves are detected daily using this technique. Beamforming is applied to determine the arrival azimuth; at a nonarray station this could be provided by poIarization analysis. The detected surface waves are associated daily with the events located by the short period array at Yellowknife, and later with the events listed in the USGS NEIC Monthly Summaries. Association requires matching both arrival time and azimuth of the Rayleigh waves. Regional calibration of group velocity and azimuth is required. . Large variations in both group velocity and azimuth corrections were found, as an example, signals from events in Fiji Tonga arrive with apparent group velocities of 2.9 3.5 krn/s and azimuths from 5 to + 40 degrees clockwise from true (great circle) azimuth, whereas signals from Kuriles Kamchatka have velocities of 2.4 2.9 km/s and azimuths off by 35 to 0 degrees. After applying the regional corrections, surface waves are considered associated if the arrival time matches to within 0.25 km/s in apparent group velocity and the azimuth is within 30 degrees of the median expected. Over the 18 month period studied, 32% of the automatically detected surface waves were associated with events located by the Yellowknife short period array, and 34% (1591) with NEIC events; there is about 70% overlap between the two sets of events. Had the automatic detections been reported to the USGS, YKA would have ranked second (after LZH) in terms of numbers of associated surface waves for the study period of April 1991 to September 1992.


2017 ◽  
Vol 120 (3) ◽  
pp. 341-350 ◽  
Author(s):  
L.J. Bezuidenhout ◽  
M. Doucouré ◽  
V. Wagener ◽  
M. de Wit ◽  
A. Mordret ◽  
...  

Abstract The Karoo region of South Africa is an ideal laboratory to use ambient seismic signals to map the shallow subsurface, as it is a quiet and pristine environment with a geology that is relatively well known. Ambient seismic signals were continuously recorded for a ten week period between August and October 2015. The ambient seismic noise network consisted of two groups of 17 temporary, stand-alone seismic stations each. These were installed in the southeastern Cape Karoo region, near the town of Jansenville. Here we present data on the retrieval and coherency of Rayleigh surface waves extracted from the vertical component recordings. We reconstruct and show, for the first time in the southeastern Cape Karoo, estimates of Green's function from cross-correlating ambient noise data between stations pairs, which can be successfully used to image the subsurface. The stacked cross-correlations between all station pairs show clear arrivals of the Rayleigh surface waves. The group velocities of the Rayleigh waves in the 3 to 7 seconds period range were picked and inverted to compute the 2-D group velocity maps. The resulting 2-D group velocity maps at different periods resulted in a group velocity model from approximately 2 to 7 km depth, which shows a high velocity anomaly in the north of the study area, most likely imaging the denser, thick sedimentary basin of the Karoo (Carboniferous-Permian). To the south, the low velocity anomaly could correspond to the overlying Jurassic-Cretaceous sedimentary sequences of the younger Algoa Basin (Uitenhage Group).


Author(s):  
Youn-Ho Cho ◽  
Yong-Kwon Kim ◽  
Ik-Keun Park

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.


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