Search Results (2,310)

Conventionally designed piezoelectric micro-electro-mechanical systems (MEMS) speakers with thin-film-type, piston-type, and cantilever-type vibration membranes still adopt a Si supporting layer, which not only hinders the improvement of sound pressure level (SPL) but also lacks characterization of reliability. In this paper, we propose a fixed-end beam–cantilever piezoelectric MEMS speaker with a flexible supporting layer, achieving an SPL comparable to that of traditional three types of piezoelectric MEMS speakers with a Si supporting layer, and displaying good reliability. The measured results performed on encapsulated prototypes mounted to an acoustic test adaptor demonstrate that under a driving voltage of 1 V_rms, the SPL exceeds 51.6 dB in the human audible frequency range of 20 Hz–20 kHz, the total harmonic distortion (THD) remains below 3.4% above 430 Hz, satisfying the basic requirements for human auditory perception. Moreover, further experiments also prove its reliability by revealing no abnormal sound output, no fracture after being dropped from heights of 1 to 5 m, and the retention of over 92% SPL following 100 h of continuous music playback. This fixed-end beam–cantilever piezoelectric MEMS speakers with a flexible supporting layer provide researchers and enterprises with brand-new design ideas and a fresh perspective, which may potentially promote their development and practical application. Full article

Reservoir boundary distance measurement is a key technology in geosteering drilling. In this field, it is difficult to balance detection precision and depth. This paper proposes a method to measure reservoir boundary distance using a drill-attached impulse sound source equipped with a reflector. The COMSOL Multiphysics (COMSOL) is used to construct a while-drilling reservoir model with a reflector and verify the model’s effectiveness through the real-axis integration method. Under this model, the dimensions of the reflector are analyzed, the relative ranging error under different distances is calculated, and source distance combinations and reservoir interface dip angles are considered. Moreover, the effectiveness of this method is verified through the results of ranging for two sets of actual geological parameters. These results show that the rotating parabolic reflector (depth 45 mm, opening radius 12.2 mm) has a good energy bunching effect. When the dominant excitation frequency of the sound source is 8 kHz, and the source distance combination is 2 m and 4 m, the minimum relative ranging error for the reservoir boundary at 7 m is 2.1%. The relative error becomes smaller when the reservoir boundary dip angle and source distance are smaller. When the source distance is 2 m or 7 m, and the dip angle is between [−20, 20] degrees, the relative error is below 15%. Simulations with actual formation parameters indicate that the proposed method attains good ranging precision. Full article

This study employed an integrated experimental–computational methodology to investigate the critical role of the layer-stacking sequence in the acoustic performance of multi-layer porous materials for vehicle NVH applications. The acoustic properties of four distinct single-layer materials were first characterized via impedance tube measurements. A finite element simulation model based on the Johnson–Champoux–Allard (JCA) theory was subsequently developed in COMSOL Multiphysics 6.2 and rigorously validated. Leveraging this validated model, a systematic analysis was conducted on six different layer sequences under a fixed total thickness of 30 mm. The simulation results showed excellent agreement with experimental data, with a root-mean-square error (RMSE) below 5%. It was demonstrated that the stacking sequence significantly governed the mid-to-high frequency sound absorption behavior, which was strongly correlated with the modulation of the real and imaginary parts of the normalized surface acoustic impedance. This study thus demonstrated that the layer sequence—a previously underexplored design factor—critically determines the absorption performance of multi-layer materials at a fixed total thickness. A full design-space analysis revealed that performance shifts are governed by changes in interfacial acoustic impedance. This physics-driven insight provides a practical framework for tailoring absorbers to specific frequency bands, offering a viable path toward lightweight acoustic solutions for electric vehicle applications. Full article

Unlike classical multi-layered micro-perforated panels (MPPs), which rely on sub-millimeter orifices for sound dissipation, we propose a multi-layered porous Helmholtz resonators absorber. It consists of alternately layered perforated porous material panels and perforated rigid panels with millimeter- to centimeter-scale orifices, primarily relying on porous materials for sound energy dissipation. Theoretically, perforated porous material panels are modeled as homogeneous fluid layers using double porosity theory, and the total surface impedance is derived through bottom-to-top impedance translation. A double-layered prototype was tested to validate the theoretical and numerical models, achieving near-perfect absorption peaks at 262 Hz and 774 Hz, with a subwavelength total thickness of 11 cm and a broadband absorption above an absorption coefficient of 0.7 from 202 Hz to 1076 Hz. Simulations of sound pressure, particle velocity, power dissipation, and sound intensity flow confirm that Helmholtz resonances in each layer enhance sound entry into resistive porous materials, causing absorption peaks. Parameter studies show this absorber maintains high absorption peaks across wide ranges of orifice diameters and panel thicknesses. Finally, an optimized triple-layer porous Helmholtz resonators absorber achieves an ultra-broadband absorption above a coefficient of 0.95 from 280 Hz to 1349 Hz with only 16.5 mm thickness. Compared with conventional MPPs, this design features significantly larger orifices that are easier to fabricate and less susceptible to blockage in harsh environments, offering an alternative solution for low-frequency and broadband sound absorption. Full article

Infrasound, physically defined as sound at frequencies below 20 Hertz, can travel long distances with minimal attenuation and permeate biological tissues due to its marked particle displacement and deep penetration. Generated by both natural phenomena and human-made systems, infrasound has drawn increasing scientific and public attention regarding its potential physiological and psychological effects. Experimental studies demonstrate that infrasound can modulate mechanosensitive structures at the cellular level, particularly pressure-sensitive ion channels such as PIEZO1 and TRPV4, leading to intracellular calcium influx, oxidative stress, altered intercellular communication, and in some settings, apoptosis. These responses vary according to sound pressure levels, frequencies, exposure duration, and tissue type. In the cardiovascular system, higher sound pressures have been associated with mitochondrial injury and fibrosis, whereas low sound pressures may exert context-dependent protective effects. In animal models, prolonged or intense exposure to infrasound has been shown to induce neuroinflammatory responses and memory impairment. Short-term studies in humans at moderate intensities have reported minimal physiological changes, with psychological and contextual factors influencing symptom perception. Occupational environments such as factories and agricultural settings may contain elevated levels of infrasound, underscoring the importance of systematic measurements and exposure assessments. At the same time, controlled infrasound stimulation has shown potential as an adjunct modality in bone repair and tissue regeneration, highlighting its dual capacity as both a biological stressor and a possible therapeutic tool. Overall, existing data indicate that infrasound may be harmful at chronic exposure depending on intensity and frequency, yet beneficial when precisely regulated. Future research should standardize exposure metrics, refine measurement technologies, and clarify dose–response relationships to better define the health risks and therapeutic applications of infrasound. Full article

Low-frequency noise, primarily generated by transformers and electrical machinery in substations, presents considerable environmental and health risks due to its strong penetration and minimal attenuation. Conventional noise control methods often fail to effectively absorb such low-frequency sounds. In response to this challenge, acoustic metamaterials featuring unique subwavelength structures have emerged as a promising solution for absorbing low-frequency and broadband noise. This study introduces a novel sound-absorbing metamaterial that integrates parallel-connected Helmholtz resonators with a helical cavity structure. To enhance its performance across a broad frequency range, the metamaterial is optimized using a genetic algorithm. Experimental validation, based on 3D-printed samples and impedance tube measurements, demonstrates high absorption efficiency at target frequencies (100 Hz, 300 Hz, and 500–1300 Hz), with absorption coefficients exceeding 0.9. The results confirm that the metamaterial effectively reduces low-frequency core noise. This work represents a significant advancement in noise control technologies for substations, with broader implications for urban noise mitigation and environmental protection. Full article

Unsupervised anomalous sound detection aims to learn acoustic features solely from the operational sounds of normal equipment and identify potential anomalies based on these features. Recent self-supervised classification frameworks based on machine ID metadata have achieved promising results, but they still face two challenges in industrial acoustic scenarios: Log-Mel spectrograms tend to weaken high-frequency details, leading to insufficient spectral characterization, and when normal sounds from different machine IDs are highly similar, classification constraints alone struggle to form clear intra-class structures and inter-class boundaries, resulting in false positives. To address these issues, this paper proposes FGASpecNet, an anomaly detection model integrating spectral enhancement and frequency-gated attention. For feature modeling, a spectral enhancement branch is designed to explicitly supplement spectral details, while a frequency-gated attention mechanism highlights key frequency bands and temporal intervals conditioned on temporal context. Regarding loss design, a joint training strategy combining classification loss and metric learning loss is adopted. Multi-center prototypes enhance intra-class compactness and inter-class separability, improving detection performance in scenarios with similar machine IDs. Experimental results on the DCASE 2020 Challenge Task 2 for anomalous sound detection demonstrate that FGASpecNet achieves 95.04% average AUC and 89.68% pAUC, validating the effectiveness of the proposed approach. Full article

Background: Commercial broiler farms produce a large amount of litter that must be removed. Anaerobic digestion (AD) is animal manure management technology with the added benefit of producing reusable energy. Our team previously showed that the micro-aeration and sound treatment of animal manure during AD increase biogas production. However, their influence on antimicrobial resistance genes (ARGs) and bacterial virulence factor genes (VFGs) is unknown. Therefore, the objective of this study was to evaluate the effect of AD on the resistome and VFGs in poultry litter (PL) and see if the effect is modified by micro-aeration and/or sound treatments. Methods: A field experiment was conducted in four anaerobic digesters that consisted of a control (a standard AD system with no air or sound), micro-aeration, sound, and combined micro-aeration and sound treatments. Overall, 21 samples were collected and analyzed with shotgun metagenomic sequencing. The samples included digestate samples (n = 12) from the four digesters obtained at 6 (baseline, i.e., before beginning of micro-aeration and sound treatments), 23 and 42 weeks, raw PL samples (n = 4), two disks comprised of the same wood as the bedding material, an initial digestate seed sample, and two initial week 0 mix samples. Results: Across all sequence reads (n = 3190) obtained from 21 samples, over 80% of the resistome was composed of four antimicrobial classes: macrolides–lincosamides–streptogramins, tetracyclines, aminoglycosides, and glycopeptides. While the total number of ARGs declined in the control digestor, it increased over time in micro-aerated or sound-treated digesters, and their combination greatly increased the number of ARGs detected. This is a new finding, and it clearly shows that micro-aeration, sound, and their combination treatment during the anaerobic digestion of PL enriches ARGs. In contrast, sound-treated AD by itself significantly (p = 0.035) reduced the mean total ARG abundance compared to the control. The number and abundance of ARGs detected in the initial digestate and PL were lower than those in the AD samples, indicating their enrichment during the AD process. On the other hand, although the AD samples had a lower frequency and abundance of VFGs than the PL, AD did not completely remove the VFGs, and their detection frequency increased over time. While micro-aeration increased the abundance of VFGs compared to the control, this effect was countered by its combination with sound treatment, offering a good animal manure treatment strategy to reduce bacterial VFGs. Conclusions: Although additional research may be required, it was shown that while sound treatment may enrich the occurrence of ARGs, it seems promising to reduce the abundance of ARGs and VFGs during the AD of PL. On the other hand, micro-aeration, alone or when combined with sound treatment, increases the abundance of both ARGs and VFGs. Moreover, the study showed that AD, with or without micro-aeration and sound treatment, is not effective for the complete removal of ARGs and VFGs from poultry litter. Rather, AD systems may act as a hotspot for ARGs, and post-AD treatments such as composting need to be evaluated. Full article

Rock geotechnical properties can be reflected in drill signals while drill rod penetrates through rocks. The rate of penetration, rotary speed, torque, load, sound, vibration, etc., are different for various rock types, since they are influenced by rock properties. Therefore, a close analysis and derivations of these drill signals can provide valuable insights into rock geotechnical properties. The drill returned signals from the mechanical sensors; for example, torque and load are commonly interpreted to characterize the rock properties. There are still limitations to such sensors and interpretation methodologies that can confidently characterize rock properties. In this research, mechanical sensors were compared and complemented with seismic sensors, for example, accelerometers and geophones, to characterize rocks and interfaces. This paper presents experimental results conducted with synthetic rock samples using mechanical and seismic sensors with a field scale drilling machine. The results show that seismic sensors can identify voids or weak (fractured) interfaces clearly compared to mechanical sensors. Smaller gaps have smaller span of low frequency and vice versa. The sensors attached to the drill head were less sensitive than the sensors attached to the sample. Drill signals showed the capacity to effectively identify material interfaces and weak fractures up to 4 mm thick, with geophones providing clearer data than accelerometers. Neither sensor distinguished fractured zones from voids. Sensors mounted directly on the sample were more sensitive than those attached to the drill head, likely due to vibration-induced signal attenuation at the drill head. Full article

To address the low-speed starting noise in a small electric vehicle, this study proposes and validates a systematic diagnostic and optimization methodology. A novel objective testing method, based on energy tracking and matching, is first employed for precise noise source localization. Combined with electromagnetic force wave analysis, this method identifies the coupling between a 24th-order motor excitation and a powertrain structural mode as the root cause. Subsequently, a low-cost, integrated optimization scheme is presented, which synergistically combines three strategies: motor control refinement, powertrain natural frequency tuning, and mount isolation enhancement. Experimental validation demonstrates that this multi-domain approach reduces the sound pressure level at the driver’s ear by 4–6 dB(A), effectively eliminating the abnormal audible noise during starting and significantly improving the in-cabin sound quality. This paper offers a cost-effective engineering framework for resolving low-speed, low-frequency noise problems in electric vehicles. Full article

Chronic respiratory diseases, the third leading cause of mortality on a global scale, can be diagnosed at an early stage through non-invasive auscultation. However, effective manual differentiation of lung sounds (LSs) requires not only sharp auditory skills but also significant clinical experience. With technological advancements, artificial intelligence (AI) has demonstrated the capability to distinguish LSs with accuracy comparable to or surpassing that of human experts. This study broadly compares the methods used in AI-based LSs classification. Firstly, respiratory cycles—consisting of inhalation and exhalation parts in LSs of different lengths depending on individual variability, obtained and labelled under expert guidance—were automatically detected using a series of signal processing procedures and a database was obtained in this way. This database of common LSs was then classified using various time-frequency representations such as spectrograms, scalograms, Mel-spectrograms and gammatonegrams for comparison. The utilisation of proven, convolutional neural network (CNN)-based pre-trained models through the application of transfer learning facilitated the comparison, thereby enabling the acquisition of the features to be employed in the classification process. The performances of CNN, CNN and Long Short-Term Memory (LSTM) hybrid architecture and support vector machine methods were compared in the classification process. When the spectral structure of gammatonegrams, which capture the spectral structure of signals in the low-frequency range with high fidelity and their noise-resistant structures, is combined with a CNN architecture, the best classification accuracy of 97.3% ± 1.9 is obtained. Full article

Sound reproduction is the electro-mechanical re-creation of sound waves using analogue and digital audio equipment. Although sound reproduction implies that repeated acoustical events are close to identical, numerous fixed and variable conditions affect the acoustic result. To arrive at a better understanding of the magnitude of deviations in sound reproduction, amplitude deviation and phase distortion of a sound signal were measured at various reproduction stages and compared under a set of controlled acoustical conditions, one condition being the presence of a human subject in the acoustic test environment. Deviations in electroacoustic reproduction were smaller than ±0.2 dB amplitude and ±3 degrees phase shift when comparing trials recorded on the same day (Δt < 8 h, mean uncertainty $u$ = 1.58%). Deviations increased significantly with greater than two times the amplitude and three times the phase shift when comparing trials recorded on different days (Δt > 16 h, $u$ = 4.63%). Deviations further increased significantly with greater than 15 times the amplitude and the phase shift when a human subject was present in the acoustic environment ($u$ = 24.64%). For the first time, this study shows that the human body does not merely absorb but can also cause amplification of sound energy. The degree of attenuation or amplification per frequency shows complex variance depending on the type of reproduction and the subject, indicating a nonlinear dynamic interaction. The findings of this study may serve as a reference to update acoustical standards and improve accuracy and reliability of sound reproduction and its application in measurements, diagnostics and therapeutic methods. Full article

Modern, electrically operated heat pumps are characterized by a high degree of efficiency and represent an attractive alternative to conventional heating systems. However, the noise emissions from heat pumps installed outside can lead to increasing noise pollution in densely populated residential areas, which represents an obstacle to widespread use. As part of a research project, a heat pump mock-up was built based on an outdoor unit in the Fraunhofer IBP. With this mock-up, investigations have now been carried out with a prototypical silencer–resonator concept. The aim was to reduce the sound power on the outlet side of the heat pump mock-up. To estimate the effect of this silencer–resonator concept for heat pumps, FEM simulations were first carried out using COMSOL Multiphysics^® with a simplified model. The simulation results validated the silencer–resonator concept for heat pumps and indicated the considerable potential for sound reduction. A measurement was then set up, with which different silencer lengths and absorber thicknesses in the silencer were tested. The measured sound attenuation was higher than the simulated values. The results showed that porous absorbers with sufficient thickness can achieve effective performance in the mid-frequency range. A maximum sound power reduction of 5.7 dB was achieved with the 0.15 m absorber. Additionally, Helmholtz resonators were implemented to attenuate the low-frequency range and tonal peaks. With these resonators sound attenuation was increased to 7.7 dB. Full article

With the increasing frequency extreme weather events associated with climate change, real-time monitoring of rainfall intensity is critical for water resource management, disaster warning, and other applications. Traditional methods, such as ground-based rain gauges, radar, and satellites, face challenges like high costs, low resolution, and monitoring gaps. This study proposes a novel real-time rainfall intensity monitoring method based on deep learning and audio signal processing, using acoustic features from rainfall to predict intensity. Conducted in the semi-arid region of Northwest China, the study employed a custom-designed sound collection device to capture acoustic signals from raindrop-surface interactions. The method, combining multi-feature extraction and regression modeling, accurately predicted rainfall intensity. Experimental results revealed a strong linear relationship between sound pressure and rainfall intensity (r = 0.916, R² = 0.838), with clear nonlinear enhancement of acoustic energy during heavy rainfall. Compared to traditional methods like CML and radio link techniques, the acoustic approach offers advantages in cost, high-density deployment, and adaptability to complex terrain. Despite some limitations, including regional and seasonal biases, the study lays the foundation for future improvements, such as expanding sample coverage, optimizing sensor design, and incorporating multi-source data. This method holds significant potential for applications in urban drainage, agricultural irrigation, and disaster early warning. Full article

The increasing amount of multilayer packaging waste poses significant environmental challenges and calls for sustainable valorization solutions. This study aimed to investigate the acoustic properties of composite materials produced by hot-pressing multilayer waste without the addition of binders or other substances. The waste was carefully cleaned and shredded into square or strip-like geometries, and the composite material plates were compressed at different temperatures (120 °C, 125 °C, 130 °C, 135 °C, and 140 °C) under a constant pressure of 5 MPa. The sound absorption coefficients were evaluated for representative samples, with results analyzed as a function of constituent geometry and processing temperature. Experimental results indicate that the pressing temperature critically affects the internal structure of the material, while waste shape exhibits a frequency-dependent influence on the absorption coefficient. The resulting composite materials display low porosity, which limits internal sound absorption and promotes sound wave reflection, indicating that these materials are more suitable for sound insulation rather than acoustic absorption. These results highlight the potential of multilayer packaging waste-based composites as a sustainable solution for noise control applications and highlight the importance of processing parameters in tailoring their acoustic performance. Full article