Optical detection of photoacoustic pulses in thin silicon wafers

1986 ◽  
Vol 64 (9) ◽  
pp. 1330-1333 ◽  
Author(s):  
H. Sontag ◽  
A. C. Tam

The propagation of photoacoustic pulses in thin silicon wafers is studied by a probe-beam deflection method. A comparison with transducer measurements is made, which suggests the existence of a nonpropagating plate mode. A signal-to-noise analysis is carried out, and the sensitivity of this detection scheme is analyzed for the case of high-frequency broad-band detection.

1986 ◽  
Vol 40 (5) ◽  
pp. 636-641 ◽  
Author(s):  
P. G. Varlashkin ◽  
M. J. D. Low ◽  
G. A. Parodi ◽  
C. Morterra

FT-IR photoacoustic (PA) and also photothermal beam deflection (PBD) spectra were recorded with the same particulate samples (graphite, charcoal, aspirin, and silica) under the same conditions in order to compare the quality of the spectra obtainable with the two techniques. A PA cell fitted with windows for the PBD laser probe beam was used, and PA and PBD spectra of each sample were recorded at 8 cm−1 resolution at each of the four different interferometer scan velocities. Although the overall aspects of FT-IR/PA and FT-IR/PBD spectra are the same, the signal-to-noise ratios of PA spectra are appreciably better than those of PBD spectra because PBD detection is more prone to disturbance by vibration than is PA detection. Absorption bands appear at the same wavenumbers in PA and PBD spectra. However, the relative intensities of bands of PBD spectra depend on the absorptive properties of the powdered solids; with weak absorbers, some bands may not be detected at all. PAS can be used with all powders. PBDS is of little or no use for the examination of weakly absorbing powders unless they scatter IR radiation extensively.


Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.


Langmuir ◽  
2002 ◽  
Vol 18 (7) ◽  
pp. 2756-2764 ◽  
Author(s):  
C. Barbero ◽  
M. C. Miras ◽  
E. J. Calvo ◽  
R. Kötz ◽  
O. Haas

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