Current Issue : April-June Volume : 2026 Issue Number : 2 Articles : 5 Articles
Controlling low-frequency noise and achieving multi-band sound insulation remain significant challenges and have long been hot topics in industrial research. This study introduces a novel multifunctional device based on the principles of acoustic metamaterials, which not only offers high-performance sound insulation but also converts low-frequency acoustic energy into electrical energy. Through an innovative design featuring multiple local resonance design, the proposed device effectively mitigates the impact of pre-tension on the membrane, while enabling efficient multi-band sound insulation that can be finely tuned by adjusting structural parameters. Experimental results demonstrate that the device achieves a maximum sound insulation of 40 dB and an average sound insulation exceeding 25 dB within the 1000 Hz frequency range. Moreover, by utilizing its local resonance property, a triboelectric nanogenerator (TENG) is specifically designed for low-frequency acoustic– electric conversion, maintaining high performance low-frequency sound insulation while simultaneously powering small scale electronic devices. This work provides a promising approach for multi-band sound insulation and low-frequency acoustic–electric conversion, offering broad potential for industrial applications....
The dual-pulse heterodyne demodulation distributed acoustic sensing (HD-DAS) system has superior performance but is fundamentally limited by the short sensing range, which poses a significant obstacle to its application in long-distance monitoring. This paper proposes and experimentally demonstrates a novel binary-tree structure DAS (BTS-DAS) aimed at overcoming this critical limitation. By physically decoupling the long-distance transmission fiber from the final sensing part, this structure effectively expands the system’s remote sensing capability without compromising the high pulse repetition rate for high-performance measurement. We identified modulation instability (MI), rather than stimulated Brillouin scattering (SBS), as the dominant nonlinear noise source in the extended fiber chain. Through careful power management, we established an optimal launch power window. The practical feasibility of the system was verified during on-site testing, where vibrations were successfully detected over a 10 km transmission link with sensing occurring in the 250 m sensing fiber segment, achieving a low background noise of −59.79 dB ref rad/ √ Hz. This work presents a robust and scalable solution for long-range, high-performance acoustic sensing....
The slow propagation speed of acoustic waves in water leads to significant variations and random fluctuations in communication delays among underwater acoustic sensor network (UASN) nodes. Conventional deep reinforcement learning (DRL)-based underwater acoustic network access methods can adaptively adjust their parameters and improve network communication efficiency by effectively utilizing inter-node delay differences for concurrent communication. However, they still suffer from shortcomings such as not accounting for random delay fluctuations in underwater acoustic links and low learning efficiency. This paper proposes a DRL-based delay-fluctuation-resistant underwater acoustic network access method. First, delay fluctuations are integrated into the state model of deep reinforcement learning, enabling the model to adapt to delay fluctuations during learning. Then, a double deep Q-network (DDQN) is introduced, and its structure is optimized to enhance learning and decision-making in complex environments. Simulations demonstrate that the proposed method achieves an average improvement of 29.3% and 15.5% in convergence speed compared to the other two DRL-based methods under varying delay fluctuations. Furthermore, the proposed method significantly enhances the normalized throughput compared to conventional Time Division Multiple Access (TDMA) and DOTS protocols....
This data descriptor presents a compact acoustic feature dataset derived from an open simulation-based study on electric vehicle gearbox housings with different structural stiffness levels. The dataset contains band-averaged sound pressure level (SPL) features extracted from radiated noise spectra of three housing concepts—flexible, intermediate, and rigid—differing only in ribbing configuration. Frequency-domain SPL spectra in the 1–6 kHz range were partitioned into five one-kilohertz bands, yielding a five-dimensional acoustic feature vector for each housing–microphone combination. In total, twelve feature vectors are provided, accompanied by stiffness labels and metadata describing the underlying simulation context. In addition to the dataset itself, baseline exploratory analyses are reported to illustrate potential reuse scenarios. Principal component analysis and unsupervised clustering demonstrate that mid-frequency bands, particularly between 2 and 4 kHz, exhibit sensitivity to housing stiffness, whereas total integrated spectral energy shows limited discriminative power. These analyses are intended to be illustrative examples rather than predictive models, given the deliberately small dataset size. The dataset is designed for reuse in benchmarking dimensionality reduction methods, clustering algorithms, uncertainty-aware classifications, and educational demonstrations of small-sample NVH data analysis. By providing a transparent and lightweight acoustic feature representation, this contribution supports reproducible research and early-stage comparative studies in drivetrain noise and vibration analysis....
Acoustofluidics has emerged as a transformative technology for contact-free manipulation of microparticles and fluids in microscale systems. Although bulk acoustic waves (BAWs) are known to displace inhomogeneous fluids through acoustic radiation force acting at fluid interfaces, the capability of surface acoustic waves (SAWs) to produce analogous relocation phenomena remains largely unexplored. This study addresses a critical gap in acoustofluidic theory by presenting the first comprehensive finite element method investigation of SAW-driven motion of inhomogeneous fluid confined within microchannels of widths equal to one full or one-half SAWwavelength. Unlike BAW-based system that generate uniform pressure fields across channel heights, SAWdevices exhibit inherently nonuniform vertical pressure distributions and intense near-boundary streaming—features that fundamentally alter fluid relocation dynamics. Our simulations demonstrate that despite high-frequency operation (6.65 MHz) and strong ARF, standing SAW fields fail to achieve stable fluid relocation in both initially stable and unstable configurations due to vertical pressure stratification and rapid floor-level streaming. Nevertheless, these same characteristics generate vigorous transverse folding flows that enable exceptionally rapid homogenization, offering a distinct acoustofluidic mechanism for on-chip mixing. These findings not only elucidate fundamental physical differences between BAW and SAW actuation in multiphase microfluidic systems but also establish design principles for SAWinduced microfluidic mixers. The results provide crucial theoretical guidance for device optimization where rapid homogenization is desired over stable stratification....
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