Acoustic imaging using high-frequency ultrasound can be an effective survey method to clarify the distribution of asari clams, which live in a relatively shallow layer of sediment. However, the propagation of ultrasound dramatically changes depending on grain size, resulting in visibility deterioration of acoustic images. In this study, the effects of grain size on the visibility of acoustic images were investigated by experiments using glass beads. Then, the effects were discussed using theoretical attenuation models (Biot–Stoll model and multiple scattering model developed by Schwartz and Plona [J. Appl. Phys. 55, 3971 (1984)]) and time–frequency analysis based on the continuous wavelet transform (CWT). In addition, wavelet shrinkage was applied to improve the visibility of acoustic images. The results suggest that multiple scattering and velocity dispersion strongly affected the sharpness and contrast of acoustic images depending on grain size. In addition, it was found that wavelet shrinkage was effective in reducing speckle noise and increasing the visibility of acoustic images of buried asari clams.
Statistical Energy Analysis (SEA) is commonly used for the prediction of interior cabin noise from construction equipment such as excavators, dump trucks, or graders. While traditional SEA method is computationally efficient and effective for the prediction of total radiated noise,
it isn't suitable for prediction of sound diffraction around machinery and evaluation of spatial variations in sound field. As a result, prediction of cabin airborne interior noise transmission using SEA method typically requires experimental measurements in order to estimate incident sound
field over the exterior boundary of the cab which makes it unsuitable for use in early stage design where test data isn't available. A novel SEA method that accounts for spatial gradients in the reverberant field has been developed and is introduced in this paper. It's usage for prediction
of both exterior and cab interior noise over broad frequency range is demonstrated along with experimental validation for construction equipment under operating conditions.
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