Journal of the Acoustical Society of America最新文献

This study investigated the noise emission and thrust performance of a heavy-lift unmanned air vehicle (UAV) with a coaxial propulsion system that operates under differential rotor speeds. The UAV adopted an octo-quad architecture, where each rotor pair consists of two propellers with different blades, allowing independent operation of fore and aft rotors in corotating (CR) and contra-rotating (CTR) configurations. Acoustic emissions and thrust were measured under steady conditions. The study compared the performances of CR and CTR configurations and examined the influence of differential rotor speed on the noise emission of the vehicle under different loads for both configurations. The results indicate that the CTR configuration achieves a maximum load factor 0.28 higher than that of the CR configuration and features lower noise at the same thrust when employing differential rotor speed. For both configurations, the drone's noise was influenced by the aerodynamic characteristics of propellers. Specifically, increasing the fore rotor speed relative to the aft rotor amplifies the noise, whereas increasing the aft rotor speed reduces noise without compromising thrust. Corresponding noise spectra were analyzed across different load factors. The results provide insights that can inform about the optimization of noise emission and performance of UAVs with coaxial propulsion systems.

An overcomplete dictionary is constructed by combining two sparse bases, designed for the spatially sparse and extended source cases, respectively. By utilizing this dictionary, the compressive equivalent source method is expected to achieve sparse reconstruction of sound fields radiated by unknown sources. However, prior studies and numerical simulations presented in this paper reveal that an unsuitable sparse basis would be selected for sound field representation, thereby degrading reconstruction performance. To address this limitation, this paper proposes an adaptive sparse basis compressive equivalent source method by introducing joint sparsity and low-rank constraints. The method adjusts the sparse representation by formulating the reconstruction as a Bayesian optimization problem that simultaneously promotes sparsity and low-rank structures of source strength coefficients. Both numerical simulations and experimental results across three source cases demonstrate that the proposed method can effectively select suitable sparse bases. Consequently, higher reconstruction accuracy than the conventional compressive equivalent source method using the overcomplete dictionary can be achieved (particularly in spatially sparse and combined source cases). Moreover, the reconstructions obtained by the proposed method exhibit greater robustness. This method provides a solution for reconstruction without prior knowledge of source characteristics, offering practical advantages for noise source identification applications.

This study performed direct aeroacoustic simulations for two flute headjoints to clarify the mechanism by which the harmonic structure changes with jet angle (angle between jet and the mouth opening in flute playing). As jet angle is increased (jet is directed perpendicular to mouth opening), the second harmonic is intensified more than the third harmonic. This harmonic structure change occurs because the jet deflects towards the inside of the pipe with increasing jet angle, which increases the actual jet offset (relative height of jet to edge). This jet deflection was found to be caused by the pressure gradient between the inside and outside of the pipe. As jet angle was increased, the jet was directed horizontally to the inner edge wall, resulting in a decrease in the pressure inside the pipe, whereas the angle between the jet and outer edge wall increased to increase the pressure outside. When the inclination of the inner edge wall was changed to be more perpendicular to the jet, the pressure around the wall increased, and the jet was deflected further outward. The angle between the jet and the edge wall affects the jet deflection and harmonic structure.

We report results for a psycho-acoustic experiment examining Spanish vowel ([a,e,i,o,u]). recognition in speech-shaped noise (SSN) and background babble (1-16 talkers) by two listening groups: native Spanish speakers (SP group) and native English speakers (EN group). The motivation for the current study is to investigate acoustic-phonetic and informational masking (APM and IM, respectively) effects (1) on segment/phoneme recognition, and (2) by participants who do not speak the language of the target or masker (as well as native speakers of Spanish) in order to disambiguate the effects of APM and IM. For the tests, background noise, both SSN and background babble, were presented at three signal-to-noise ratios (at 0, -6, and -12 dB) while a target containing one of the five Spanish vowels was presented in the syllables [da, de, di, do, du]. Inter-group differences in response accuracy point to significant effects of APM as listening conditions erode, and minimal effects due to higher-order factors based on masker meaningfulness, semantic content, and language familiarity.

This paper addresses the challenge of underwater acoustic target detection, a critical task in marine monitoring and passive sonar systems, which is often hindered by complex noise environments and imbalanced labeled data where the targets appear very sparse in the long collected data. Traditional models take the minimization of the binary cross-entropy (BCE) as the optimization criterion. However, underwater target detection is fundamentally a class-imbalanced classification problem that uses the receiver operating characteristic curve as the evaluation metric instead of the classification accuracy, while BCE maximizes the classification accuracy on training data. To address this, three optimization methods are proposed to directly maximize the area under the receiver operating characteristic curve (AUC). Additionally, the Neyman-Pearson criterion from classical detection theory is incorporated into the AUC optimization framework, forming a curriculum learning strategy that progressively optimizes the partial area under the curve (pAUC). To overcome the scarcity of underwater data, a cross-domain knowledge transfer method is implemented from the airborne to underwater acoustic domains, which accelerates model convergence and improves generalization. Experimental results demonstrate that the proposed AUC- and pAUC-based loss functions outperform BCE and achieve state-of-the-art performance under low signal-to-noise ratio and mismatched conditions.

Super-resolution methods based on sparse recovery often suffer significant performance degradation under strong near-field interference. Existing approaches typically involve either incorporating near-field steering vectors into the dictionary or applying pre-filtering techniques. However, the former approach introduces a severe basis coherence problem, which may lead to reconstruction failure. The latter may distort the target signal, especially when the interference subspace is high-dimensional. This paper proposes a preprocessing method based on generalized eigenvalue decomposition. Inspired by the concept of matrix filtering, the method aims to maximize the output power ratio between the subspace spanned by the desired steering vectors and the interference subspace. Formally, the proposed method can be viewed as a generalized extension of the optimal beamformer to a matrix filtering framework. Unlike zero-forcing methods, it offers a balanced trade-off between interference suppression and target preservation. Moreover, the computational efficiency is significantly lower than that of conventional matrix filtering approaches that rely on convex optimization. When combined with subsequent sparse recovery algorithms, the proposed method enables super-resolution direction-of-arrival estimation even under conditions of limited snapshots and low signal-to-noise ratios. Simulation and experimental results demonstrate the effectiveness of the proposed method in handling real-world strong near-field interference while maintaining better real-time performance.

An early signal detection model featured two simplified auditory systems with contrasting sensitivity levels (low vs high) to examine the impact of different background noise conditions on the detection and recognition performance of the system. The model showed that a hypothetical animal listener communicating under variable background conditions must trade off the risk of misrecognizing the sound, incurred only adopting the high-sensitivity auditory system, with the risk of failing to detect a sound received at low amplitude, incurred only adopting the low-sensitivity one. Here, I implement the model to explore the consequences of the costs of hearing the background noise and irrelevant sounds. Results showed that both costs add to the cost of sound misrecognition to decrease the range of noise conditions favoring a high auditory sensitivity. However, their importance is strongly affected by the amount of irrelevant sounds received. When the listener receives many irrelevant sounds, the importance of the costs of hearing these sounds and hearing the background noise in particular, increases at the expense of that of the cost of misrecognition. The model also revealed that a high-sensitivity listener may be favored even in noisy environments if listening to the noise stimuli provides some benefit to the animal.

Single-beam acoustic tweezers (SBAT) use focused ultrasounds to remotely hold, move, and apply forces to objects in three dimensions. Addressing potential applications in the microscopic range requires a high frequency, since the object size scales with the acoustic wavelength. Acoustic streaming, the fluid motion induced by the acoustic attenuation of ultrasonic waves, can generate a drag force that opposes the acoustic radiation force, complicating stable manipulation. This study investigates the interplay between acoustic radiation force and the streaming-induced drag force under sharp focusing conditions for the feasibility of high-frequency SBAT. Using theoretical modeling and numerical simulations, this study examines how acoustic pressure amplitude, beam focusing, and frequency affect streaming flow and trapping stability. The results provide insights into optimizing high-frequency SBAT systems, especially in liquid environments, and should contribute to improving the precision and reliability of acoustic manipulation at the micro-scale.

Microbubbles are excellent contrast-enhancing agents for ultrasound imaging. A long shelf life with a robust size distribution is critical for their efficacy. Here, we investigated the long-term stability and attenuation of a custom-made polydisperse microbubble suspension. The microbubbles were prepared using mechanical agitation with a gas core of perfluorobutane (C4F10), and a 9:1 molar ratio mixture of 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC) and 1,2-dipalmitoyl-sn-glycero3-phosphatidylethanolamine-polyethyleneglycol-2000 (DPPE-PEG2000) lipids. Their size distribution and attenuation response were measured in regular intervals over 30 days. The size remained the same (∼2.25 μm) for the first 13 days before slightly increasing to ∼2.5 μm. The microbubble concentration decreased with time (7.14 ± 1.12 × 109 MB/mL initially and 3.29 ± 0.66 × 109 MB/mL at day 30), resulting in a corresponding decrease in attenuation. We determined the shell properties of microbubbles by applying the exponential elasticity model (EEM) to the attenuation. Like the size, the shell elasticity and viscosity remained unchanged for 13 days and then increased by ∼50% and ∼200%, respectively. The study sheds light on the shelf life and in vitro stability of lipid-coated microbubbles, offering valuable information about their effectiveness as ultrasound contrast agents.

Ambisonics is a method for capturing and rendering a sound field accurately, assuming that the acoustics of the playback room does not significantly influence the sound field. However, in practice, the acoustics of the playback room may lead to a noticeable degradation in sound quality. This paper proposes a recording and rendering method based on Ambisonics that utilizes a perceptually motivated approach to compensate for the reverberation of the playback room. The recorded direct and reverberant sound field components in the spherical harmonics domain are spectrally and spatially compensated to preserve the relevant auditory cues, including the direction of arrival of the direct sound, the spectral energy of the direct and reverberant sound components, and the interaural coherence across each auditory band. In contrast to the conventional Ambisonics, a flexible number of Ambisonics channels can be used for audio rendering. Listening test results show that the proposed method provides a perceptually accurate rendering of the originally recorded sound field, outperforming both conventional Ambisonics without compensation and even Ambisonics reproduction in a simulated anechoic room. Additionally, perceptual evaluations of listeners seated at the center of the loudspeaker array demonstrate that the method remains robust to head rotation and minor displacements.