Acoustic Emission Source Location Based on Signal Features

2006 ◽  
Vol 13-14 ◽  
pp. 77-82 ◽  
Author(s):  
Michal Blahacek ◽  
M. Chlada ◽  
Z. Prevorovský

Good knowledge of acoustic emission (AE) source location is the basic requirement for further damage mechanism characterization. Calculation of the AE source location is mostly based on arrival time differences of the signals recorded by different transducers. Error free arrival time determination is the crucial factor for the localization results accuracy together with the exact elastic wave velocity measurement. In the paper difficulties and limitations of the elastic wave velocity computation are shown. To solve the velocity and the time differences problems, new approach to AE source localization is described. The new method estimates the AE source coordinates using artificial neural network (ANN) processing extracted signal parameters. The ANN do not uses neither arrival time differences nor elastic wave velocities as input data. The new approach advantages are discussed in cases of both numerical and practical experiments. The experiments results are promising for the use of designed localization method in praxis.

Geophysics ◽  
1970 ◽  
Vol 35 (3) ◽  
pp. 387-403 ◽  
Author(s):  
E. Strick

Under the assumption of almost constant‐Q behavior of solids over a wide range of frequencies, together with some meaningful assumptions about the linear frequency behavior of the attenuation function, we have been able to obtain theoretical expressions describing the waveform distortion of an impulse‐excited plane wave as it decays and spreads on passing through large distances of the solid. When typical values for the parameters (as obtained from laboratory model or short range field experiments) for a solid having a mechanical Q of about 50 are used, the resulting waveforms at first glance appear to have a simple and not unexpected behavior. The peak amplitude of the waveform in the time domain varies roughly with the inverse of the square of the travel distance (this includes an inverse first power due to geometrical spreading). Also, a spreading of the waveform occurs that varies roughly linearly with the travel distance. This spreading is such that a positive impulse simply broadens as it travels without developing any zero crossings in its wave shape. However, it turns out that the part of the waveform leading up to the visible onset does not admit of a purely elastic interpretation, so that one cannot relate conceptually the arrival time with a purely elastic‐wave velocity. For our solid of Q≈50, about one‐seventh of the arrival time duration is due to a purely inelastic behavior; during this period of inelastic behavior the amplitude is not zero but it is deceptively small. We have designated this portion as a “pedestal.” On observing seismic records, we are never aware of this conceptual division and consequently attribute to the observed arrival an elastic wave velocity, which in our example happens to be about 15 percent less than the actual elastic wave velocity of the solid. Although the existence of the pedestal may not appear to be significant when we restrict our observations to seismic records limited in bandwidth to the low frequencies encountered in exploration or earthquake seismology, an upward curvature which is not associated with a discontinuity in the slope at the time of visual onset will remain and can be of great importance if very accurate arrival time measurements are made. This part of the pedestal can become even more important when we consider refraction arrivals, where the onset undergoes an additional time integration that further enhances the upward curvature of the pedestal.


1997 ◽  
Vol 62 (11) ◽  
pp. 1698-1709
Author(s):  
Miloslav Hartman ◽  
Zdeněk Beran ◽  
Václav Veselý ◽  
Karel Svoboda

The onset of the aggregative mode of liquid-solid fluidization was explored. The experimental findings were interpreted by means of the dynamic (elastic) wave velocity and the voidage propagation (continuity) wave velocity. For widely different systems, the mapping of regimes has been presented in terms of the Archimedes number, the Froude number and the fluid-solid density ratio. The proposed diagram also depicts the typical Geldart's Group A particles fluidized with air.


2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Tohru Watanabe ◽  
Miho Makimura ◽  
Yohei Kaiwa ◽  
Guillaume Desbois ◽  
Kenta Yoshida ◽  
...  

AbstractElastic wave velocity and electrical conductivity in a brine-saturated granitic rock were measured under confining pressures of up to 150 MPa and microstructure of pores was examined with SEM on ion-milled surfaces to understand the pores that govern electrical conduction at high pressures. The closure of cracks under pressure causes the increase in velocity and decrease in conductivity. Conductivity decreases steeply below 10 MPa and then gradually at higher pressures. Though cracks are mostly closed at the confining pressure of 150 MPa, brine must be still interconnected to show observed conductivity. SEM observation shows that some cracks have remarkable variation in aperture. The aperture varies from ~ 100 nm to ~ 3 μm along a crack. FIB–SEM observation suggests that wide aperture parts are interconnected in a crack. Both wide and narrow aperture parts work parallel as conduction paths at low pressures. At high pressures, narrow aperture parts are closed but wide aperture parts are still open to maintain conduction paths. The closure of narrow aperture parts leads to a steep decrease in conductivity, since narrow aperture parts dominate cracks. There should be cracks in various sizes in the crust: from grain boundaries to large faults. A crack must have a variation in aperture, and wide aperture parts must govern the conduction paths at depths. A simple tube model was employed to estimate the fluid volume fraction. The fluid volume fraction of 10−4–10−3 is estimated for the conductivity of 10−2 S/m. Conduction paths composed of wide aperture parts are consistent with observed moderate fluctuations (< 10%) in seismic velocity in the crust.


Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1513 ◽  
Author(s):  
Naser Golsanami ◽  
Xuepeng Zhang ◽  
Weichao Yan ◽  
Linjun Yu ◽  
Huaimin Dong ◽  
...  

Seismic data and nuclear magnetic resonance (NMR) data are two of the highly trustable kinds of information in hydrocarbon reservoir engineering. Reservoir fluids influence the elastic wave velocity and also determine the NMR response of the reservoir. The current study investigates different pore types, i.e., micro, meso, and macropores’ contribution to the elastic wave velocity using the laboratory NMR and elastic experiments on coal core samples under different fluid saturations. Once a meaningful relationship was observed in the lab, the idea was applied in the field scale and the NMR transverse relaxation time (T2) curves were synthesized artificially. This task was done by dividing the area under the T2 curve into eight porosity bins and estimating each bin’s value from the seismic attributes using neural networks (NN). Moreover, the functionality of two statistical ensembles, i.e., Bag and LSBoost, was investigated as an alternative tool to conventional estimation techniques of the petrophysical characteristics; and the results were compared with those from a deep learning network. Herein, NMR permeability was used as the estimation target and porosity was used as a benchmark to assess the reliability of the models. The final results indicated that by using the incremental porosity under the T2 curve, this curve could be synthesized using the seismic attributes. The results also proved the functionality of the selected statistical ensembles as reliable tools in the petrophysical characterization of the hydrocarbon reservoirs.


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