Journal of the Acoustical Society of America最新文献

Infrasound signal detection using arrays is an established method for detecting signals from a variety of cultural and geophysical sources. Array processing requires analysis from two or more sensors at an infrasound station. By employing array techniques, signals are isolated from various sources of noise by computing coherence between recorded signals across spatially distributed sensors at a station. Array processing requires multiple sensors and intra-array comparisons that potentially increases time required for event detection. This study presents a signal detection method utilizing deep learning to identify high-quality signals in infrasound waveforms with data from a single infrasound sensor, which might permit event discrimination without using arrays. The approach involves using audio signal processing techniques, applied to infrasound frequencies, to extract a feature space, which is then used to train a deep learning model. A 25-day continuous dataset featuring diverse infrasonic events that include potential avalanches, vehicle traffic, and explosions, collected from Little Cottonwood Canyon, Utah, USA was analyzed for this study. The data provide a convenient testbed for high-quality signal identification using single channel infrasound. The sensor network was motivated by the goal of identifying snow avalanches. Performance was assessed for an optimized model over a range of test data.

Acoustic interference patterns (AIPs) typically exhibit a regular striation structure in shallow water. However, internal solitary waves (ISWs) commonly found in the ocean can cause severe distortion in AIPs, thereby presenting significant challenges to acoustic signal processing methods reliant on AIPs. Grounded in coupled mode theory, this paper elucidates the mechanism of AIP distortion induced by ISWs. Specifically, ISWs introduce several time-varying "coupled" components while maintaining the time-invariant "adiabatic" components. Leveraging the distinct temporal characteristics of these two classes of components, this paper proposes a time-averaging processing (TAP) method. This method averages the AIPs from multiple snapshots to preserve the time-invariant "adiabatic" components while suppressing the time-varying "coupled" components. Consequently, the TAP method restores the distorted AIP to its striation structure. The efficacy of the proposed method is substantiated through validation using simulated data. Moreover, the TAP method provides a foundation for enhancing the performance of underwater acoustic signal processing methods reliant on AIPs.

We present a processing routine for marine mammal call detection and localisation, using North Atlantic right whale (NARW) upcalls and moans passively recorded by a sonobuoy grid in July 2018 in the southern Gulf of St. Lawrence, Canada. Right whales are critically endangered and at risk from ship strikes and fishing gear entanglement. We demonstrate the effectiveness of passive acoustic monitoring followed by a three-step analysis as a mitigation tool. The first step detects NARW calls using a publicly available deep learning model, trained on open acoustic datasets, adapted and optimised for the sonobuoy dataset using a smaller adaptation set. The second step applies spectrogram correlation for contact association and time difference of arrival estimates, identifying the same call across multiple sonobuoys. The third step estimates call location via nonlinear Bayesian inversion, assuming direct call propagation, yielding source positions with uncertainty estimates. This three-step analysis effectively detects and localises NARW upcalls, especially from within or near the sonobuoy grid. It enhances information compared to visual surveys and provides realistic uncertainty estimates, supporting its role in conservation and management efforts.

Sandwich cylindrical shells with porous polymeric foam cores and periodically distributed stiffeners are attractive candidates for lightweight control of surrounding acoustic pressure, yet their acoustic scattering in realistic multilayered configurations remains poorly characterized. This study develops an analytical framework for predicting the total scattering cross section of a sandwich cylindrical shell under oblique plane wave incidence for a specific configuration combining a functionally graded (FG) outer facesheet, an FG open-cell porous polymeric foam core, an isotropic inner layer separated by air gaps, orthogrid (ring-string) stiffeners, and coupled interior and exterior acoustic fluids. Structural dynamics are modeled using first-order shear deformation theory and Hamilton's principle, while the foam core is treated as an FG viscoelastic medium with a frequency-dependent complex modulus. Continuity of acoustic pressure and normal velocity at the fluid-structure interfaces couples the interior and exterior acoustic fields and yields the scattered pressure and total scattering cross section. Numerical results show that periodic ring-string stiffening strongly attenuates low-frequency resonances and shifts the first major scattering peak to higher frequencies, thereby reducing low-frequency scattering levels. The stiffened configuration also reduces the peak magnitude of the surrounding acoustic pressure (from approximately ±1.5 Pa to ±1.0 Pa at 10 kHz), indicating a weaker scattered field.

Acoustic metamaterials are a class of architected materials with dynamic properties that are designed at the sub-wavelength scale to achieve exotic or unique macroscopic response. Although early concepts of acoustic metamaterials relied on static configurations, recent research has further expanded the limits of acoustic customization by incorporating active or tunable responses. This article provides an introduction to the special issues of The Journal of the Acoustical Society of America and JASA Express Letters on active and tunable acoustic metamaterials and begins with a brief description of the general categories of active control and tunable response included in the contributions to the special issue and, then, provides a brief description of the articles in this special issue, grouped by general category, and how the research presented in these works contribute to the advancement of acoustic metamaterial research.

Conventional passive earmuffs, which have a single number rating (SNR) of 28-32 dB, can effectively protect users' hearing but block useful lower-intensity sound waves, such as speech, causing communication difficulties. This leads employees to remove their earmuffs to comprehend important information or to avoid miscommunication while wearing earmuffs, which might lead to accidents. This problem can be solved using pressure level-dependent passive earmuffs with selective frequency and intensity filtration to allow lower intensity waves (such as speech) to pass through while blocking high-intensity waves (hazardous noise). This study evaluates speech intelligibility and hearing protection of an in-house developed pressure level-dependent passive earmuff prototype made of shape memory metamaterial inserts. Hearing protection and speech intelligibility were evaluated in a controlled environment. Numerical simulations of earcups and inserts were performed to optimize their design and obtain the required noise reduction at various intensities. The prototype can ensure an in-ear sound pressure level of less than 82 dB (across frequencies) up to 110 dB pink noise. The prototype exhibits fair speech intelligibility in both quiet and noisy environments. User-experience feedback indicated that 85% of the participants preferred the shape memory metamaterial earmuffs over commercially available earmuffs, for use in diverse working environments.

Voice, or phonation quality, is a central concept across multiple domains of phonetic theory. However, the acoustic measurements used to quantify voice quality are far from straightforward. Recently, Chai and Garellek [J. Acoust. Soc. Am. 152(3), 1856-1870 (2022)] proposed residual H1* as an improvement over the oft-used H1*-H2* measure. Here, this Letter raises concerns about the robustness of their conclusion due to incomplete random-effect structures in their models. The Letter suggests that reducing descriptions of voice quality to a single measure might not be adequate and multiple measures are needed to capture the inherent multidimensionality of voice quality.

The Reflections series takes a look back on historical articles from The Journal of the Acoustical Society of America that have had a significant impact on the science and practice of acoustics.

This study presents performance predictions and selection strategies for different generations of single crystals to guide the application of single-crystal face-plated 2-2 piezocomposites in deep-water hydrophones. Accordingly, the home-built setups were developed for measuring the parameter variation of three generations of single crystals under uniaxial stress. Based on this foundation, a stress-dependent static equilibrium model for face-plated 2-2 piezocomposites was established. The stress-dependent parameters were incorporated into the model to evaluate the performance of face-plated 2-2 piezocomposite hydrophones. Furthermore, a finite element model including the stress-dependent parameters was established to verify the effectiveness and enhance the accuracy of the prediction. The results show that the receiving voltage sensitivity (RVS) of the hydrophone using PMN-PT single-crystal piezocomposites tends to be better under uniaxial stress within the range of 0.6-1.8 MPa, while for Mn:PIN-PMN-PT, the RVS decreases by no more than 6 dB until the stress reaches 4 MPa. In conclusion, the PMN-PT single crystal is advantageous for hydrophones operating under uniaxial stress below 200 m, whereas the Mn:PIN-PMN-PT single crystal is more suitable for deep-water hydrophone applications due to its stable piezoelectric performance.

In brass instrument playing, mouthpiece force (MPF) contributes to sound production while preventing air leakage and assisting embouchure function. The MPF consists of a minimum force to produce sound and a margin force as a safety measure. This study investigated the effects of pitch and dynamics of the sound produced on the French horn on the MPF and those two force constituents. Eleven professional players played long F2, F3, F4, Bb4, and F5 tones at p, mf, and f using an MPF sensor-equipped mouthpiece (MP). The MPF increased significantly with pitch and dynamics, from an average of 5 N for F2 to 40 N for F5 at mf, with inter-player differences at F5 from 16 to 73 N. The minimum and margin forces also increased with pitch and dynamics, with a large inter-player variation. For all pitches and dynamics, the margin force as a percentage of MPF ranged from 35% to 57%, much larger than that reported in an earlier trumpet study. This relatively high margin setting is considered a French-horn playing strategy, ensuring airtightness against thin-rimmed MPs, assisting embouchure function by tightening the boundary of the lip vibration area with the rim, and may also help increase lip tension.