Search Results (371)

Sound source localization based on microphone arrays has attracted extensive research interest in the fields of speech communication, detection and tracking. However, conventional near-field beamforming typically assumes free-field propagation and ignores coherent ground reflections, which bias phase estimates at floor-mounted arrays and degrade localization accuracy. To address this, the total Green’s function is reformulated by embedding the image-source reflected path directly into the beamforming propagation model. Unlike conventional approaches that assume free-field propagation, this formulation enables phase compensation to jointly account for the direct and ground-reflected wavefronts. The in-phase superposition of signals is then realized through frequency-domain phase compensation, and the sound source position is estimated via the maximum likelihood criterion. Subsequently, a dual-mode operation mechanism of automatic broadband scanning and manual single-frequency analysis is implemented, with frequency-weighted wideband spatial spectrum processing for noise and aliasing suppression. Finally, a real-time sound source localization system based on a 4 × 4 MEMS array is designed. Experimental results show that sound source localization in a broad frequency band can be achieved at standoff distances of 0.1 m–0.3 m from the array plane, with a localization accuracy of less than 0.015 m. The proposed method demonstrates strong robustness against ground-reflection interference and has potential applications in acoustic monitoring, industrial fault diagnosis and other related areas. Full article

Construction noise assessment commonly assumes that the source location is already known, which limits its applicability when active equipment cannot be accessed or precisely surveyed. This study proposes a transparent inverse acoustic model for jointly estimating the location and time-dependent sound pressure level (SPL) of a pile-driving source from synchronized field measurements. Noise was recorded for 5 s at five GNSS-defined receiver positions on a construction site in Astana, Kazakhstan, producing 40 SPL values per receiver at 0.125 s intervals. The model applied spherical geometrical spreading and identified the source position by minimizing the disagreement among the distance-corrected source levels obtained from the receivers. The source was estimated at local coordinates [56.6, 113.8] m, with a Monte Carlo sensitivity analysis indicating a 95% confidence region of approximately 5–8 m under combined receiver-coordinate and SPL-measurement uncertainty. Its reconstructed SPL ranged from 81.6 to 99.9 dB(A) at the 1 m reference distance, while the equivalent source SPL was 90.4 dB(A). The measured impulsive pattern was preserved in the reconstructed source history, with dominant peaks occurring at approximately 1 s intervals. Comparison of measured and predicted receiver levels yielded an overall MAE of 1.3 dB(A) and RMSE of 1.6 dB(A), reflecting internal consistency between measured and reconstructed receiver levels. The as-driven pile position was subsequently surveyed independently, giving a true localization error of 2.3 m for the estimated position, within the 95% confidence region above. Out-of-sample cross-validation and synthetic sweep across the search zone further characterize the method’s identifiability and its expected sensitivity away from the search-zone center. Full article

The ability to detect and localize the direction of the source of sounds has been with humans since ancient times, as humans can tell the direction of the sound coming from both the horizontal plane and vertical plane. Recent theory on why humans can distinguish the direction of the sound in the vertical plane is due to the difference between sounds reflected in human ears, more specifically, the pinna, which distort the sound in both the frequency domain and the time domain. In this paper, we will explore more on how to use the distortion in the time domain to localize the sound in the vertical plane. By analyzing the sound that is reflected in one of the artificial ears in the time domain, we use those data as a model to determine the sound coming from the vertical plane. The average angular error of the model is 4.86 degrees, with an RMSE of 6.90. The result confirms that we can analyze the sound in the time domain to determine the sound source direction in the vertical plane analyzed from only one microphone in the artificial ear. Full article

This study investigates the under-explored contribution of internal radial stress to macroscopic gravitational potentials. We utilize a novel, precision-damped torsion balance apparatus designed to isolate and measure gravitational perturbations induced by radial stress within rapidly rotating macroscopic masses, rigorously controlling for acoustic, thermal, and electromagnetic variables. Our findings document an anisotropic mechanical influence along the plane of rotation that exceeds standard weak-field gravitational predictions. The measured apparatus potential exhibits a kinematic scaling ($\propto {\omega }^4$) consistent with a linear torsion spring responding to an underlying quadratic (${\omega }^2$) driving force. While active Herzan leveling, counter-rotating geometry, and precision balancing successfully eliminated bulk frame-drag and mechanical vibration, this atmospheric baseline study concedes that the persistent ${\omega }^2$ force may still be masked by complex, non-linear fluid dynamic asymmetries. Consequently, this paper establishes a ‘Stage 1’ methodological baseline, mapping the absolute limits of atmospheric testing and defining the engineering prerequisites for future high-vacuum gravitational extractions. Isolating this residual force in a future high-vacuum environment is imperative. Should such testing confirm the signal is gravitationally sourced, this anisotropy suggests a potential coupling between the internal stress-energy tensor and the local spacetime metric that is not fully accounted for in standard linear approximations. If this phenomenological stress-metric coupling can be isolated and shown to scale macroscopically, it could theoretically provide a non-linear mechanism for observed rotational gravitational symmetry breaking. The speculative astrophysical implications of such a coupling are also discussed. Full article

Cross-condition fault identification for crane slewing bearings is difficult because low rotational speed, heavy loading, and operating-condition variation jointly weaken fault-induced impulses and alter the distribution of monitoring data. In addition, vibration and acoustic emission signals describe different aspects of bearing degradation, making fixed multi-sensor fusion insufficient when sensor sensitivity changes across fault states. This study proposes a Lightweight Domain-Adaptive Graph Convolutional Network (LDAGCN) for cross-condition diagnosis. The model uses six vibration channels and one acoustic emission channel as synchronized heterogeneous inputs. Two compact one-dimensional encoders first learn modality-specific temporal representations, after which a feature-wise gate determines the relative contribution of each sensing modality. The fused embeddings in every mini-batch are regarded as graph nodes, and a sparse sample graph is reconstructed from Top-k cosine similarities. Multi-receptive-field graph convolution then aggregates one-hop and higher-order neighborhood information, while a residual connection limits excessive modification of the original fused features. To reduce the discrepancy between operating conditions, the training objective combines source-domain classification, adversarial domain discrimination, maximum mean discrepancy, and supervision from a small labeled target-domain adaptation subset. Experiments were carried out on a dedicated crane slewing-bearing test rig containing normal, inner-race fault, outer-race fault, and B1 localized-fault states. On the target-condition test set, LDAGCN achieved an accuracy of 97.22%, a Macro-F1 score of 97.21%, a Macro-Precision of 97.37%, and a Macro-Recall of 97.22%. The proposed model also outperformed 1D-CNN, ResNet1D, CNN-LSTM, DANN, MMD-DAN, and DeepCORAL under the same data partition. The confusion matrix and t-SNE projection indicate that the learned representation reduces the source–target distribution gap while retaining fault-class separation. The ablation results further indicate that the acoustic emission information, gated fusion, graph-based association learning, and domain adaptation complement each other in terms of the final diagnostic performance, while maintaining a lightweight architecture that is suitable for practical monitoring. Full article

The search and discovery of underwater shipwreck sites represent the most arduous and critical phases of underwater archaeology. Wooden shipwrecks, in particular, are characterized by low acoustic impedance contrast and weak magnetic anomalies, coupled with their limited physical dimensions. Consequently, they predominantly exist as shallow-buried, discontinuous small targets scattered within confined areas, making their detection exceptionally challenging. Furthermore, the complexity of the submarine environment—including rugged topography, turbid water columns, and strong currents—poses formidable obstacles to the effective detection of these archaeological remains. Single geophysical methods are often limited by insufficient imaging resolution, interpretation ambiguity, and geological noise, making precise localization and characterization difficult. Focusing on the Nan’ao I Ming Dynasty shipwreck located in waters approximately 24 m deep off the coast of Nan’ao, Guangdong Province, China, this study proposes and validates an “acoustic-magnetic” multi-source data integration detection method. This approach systematically integrates high-resolution multibeam echo sounding (MBES), side-scan sonar (SSS), sub-bottom profiling (SBP), and marine magnetic data to establish a comprehensive framework for identification and integration analysis. The results indicate that the MBES bathymetric data reveal a regular, elongated structure oriented north–south (approximately 34 m × 12 m), closely matching the main hull and deck configuration. The SSS imagery exhibited high backscatter intensity and parallel linear textures, effectively delineating the hard shipwreck structure and the associated rigid protective frame employed for in situ preservation. SBP data confirmed the semi-buried state of the shipwreck (burial depth of approximately 0.6 m). Spatial variations in sediment thickness around the site suggested ongoing modification by strong hydrodynamic processes. Marine magnetic surveys identified localized negative anomalies (−210 nT relative to the ambient magnetic field), contrasting sharply with the positive anomalies of the surrounding natural reefs, thereby indicating an artificial ferromagnetic source. The spatial registration and feature superposition of multi-source data facilitated the characterization of the shipwreck, demonstrating its potential to mitigate environmental interference and enhance detection reliability in this complex environment. Using the Nan’ao I shipwreck site as a case study, this study provides a detailed characterization of the site’s 3D morphology, burial state, and physical properties. The proposed methodology offers a practical and robust technical solution for underwater shipwreck archaeology in complex nearshore environments, providing significant implications for proactive discovery, efficient investigation, and protection of underwater cultural heritage (UCH). Full article

Water leakage in water supply pipeline networks leads to water resource loss, drinking water contamination, and ground subsidence. The existing acoustic leak detection techniques are constrained by low signal-to-noise ratios of leakage signals, difficulties in wave velocity estimation, and rapid signal attenuation, often resulting in localization errors of several meters. This study proposes a “wavenumber–frequency spectrum filtering and phase analysis” method for leak source localization, achieving precise positioning of underground water pipeline leaks through surface-mounted sensor array sampling. Based on the numerical simulation results, this research reveals the wavenumber–frequency spectrum characteristics of leakage noise on the ground surface, analyzes the impact of the sampling strategies on the wavenumber extraction, and ultimately constructs a localization model suitable for near-field array sampling. A mean localization error of 0.0374 m was achieved in a controlled experiment under single-layer sandy soil conditions, demonstrating the feasibility and accuracy of the proposed method under these tested conditions and providing a promising basis for precise leak localization in water supply networks that warrants further field validation. Full article

Towed hydrophone arrays are widely employed for underwater target detection and direction-of-arrival (DOA) estimation. However, array shape distortion induced by ocean currents, internal waves, and platform maneuvers severely degrades beamforming performance and DOA estimation accuracy. In this paper, a novel Bayesian fusion framework is proposed to achieve robust array shape estimation. Specifically, based on the time-delay estimates derived from the phase differences of line-spectrum components in a pre-processing step, the array geometry is first reconstructed via a piecewise straight-line fitting method. Concurrently, an existing hidden Markov model (HMM)-based method is adopted to estimate the inter-segment deviation angles, in which the smoothness of the array shape is enforced through the state-transition probabilities. The proposed framework then treats these two preliminary estimates as observations from distinct sources and incorporates a smoothness prior within a maximum a posteriori (MAP) formulation that admits a non-iterative closed-form solution to enforce physical continuity constraints on the array geometry. By fusing these complementary estimates, the proposed method simultaneously preserves local sensitivity to fine-scale bends and maintains global consistency of the array shape. Both simulation and lake-trial experiments validate the effectiveness of the proposed method, reducing the array shape estimation error by more than 30% relative to representative existing methods. Moreover, by relying solely on the received acoustic data, the method lowers the dependence on auxiliary sensors and the associated system cost. Full article

Passive localization of broadband impulsive sources in shallow water is particularly challenging when using a single hydrophone, especially over a sloping seabed. This study presents a novel single-hydrophone localization method for broadband impulsive sources in sloping shallow water. The approach utilizes warping-transformed eigenfrequencies derived from the energy density function of received signals. A key innovation is the method’s capability for simultaneous range and depth estimation in sloping seabed environments, achieved through eigenfrequency pattern matching for range estimation and normalized amplitude matching for depth estimation. The method depends primarily on waveguide depth and average sound speed, enabling robust estimation while exhibiting inherent insensitivity to variations in other environmental parameters. Both simulated and experimental data from a winter sea trial in the East China Sea validate the performance of this dual-parameter estimation approach. The results demonstrate practical applicability for underwater acoustic monitoring and remote sensing in challenging shallow water environments with complex seabed topography. Full article

Low-resource written-query keyword spotting detects a text-specified target in speech without spoken enrollment or full automatic speech recognition. We present Tibetan Phonology-Aware Speech Evidence Matching (Tibetan-PASEM), a method that encodes graphemic, approximate phonological, and dialect-related query information, matches it with local acoustic windows, aggregates window-level evidence, and applies a validation-selected operating point. Querybank198 contains 198 Tibetan written queries derived from four public speech resources. A complete-file and decoded pulse-code modulation (PCM) audit produced a corrected 213,128-pair evaluation with no identified recording-content, source-qualified speaker, or session-proxy overlap across the development-to-held-out boundary. In a three-seed corrected-index re-evaluation, the acoustically strengthened PASEM (PASEM-AS) achieved F1 scores of 66.16 ± 2.14% on seen_test, 26.51 ± 3.42% on unseen_test, and 72.10 ± 1.39% on the confusable-negative diagnostic condition, which comprises 20 training-exposed query forms and is used for negative-set analysis rather than difficulty ranking. Under the original pre-correction pair index, PASEM with transfer regularization (PASEM-TR) increased the unseen_test F1 from 25.80 ± 2.71% to 35.25 ± 4.17% and the Recall from 18.48 ± 2.98% to 33.85 ± 8.22%; the corresponding seed-level 95% confidence intervals were 24.89–45.61% and 13.43–54.27%. These results establish strong familiar-query discrimination, an audited fixed-threshold evaluation protocol, and partial, seed-sensitive transfer to held-out written queries. Full article

High-precision, long-endurance navigation remains a central bottleneck for autonomous underwater vehicles (AUVs) operating in GNSS-denied, acoustically constrained, and dynamically disturbed marine environments. This manuscript examines the complete sensing-mapping-estimation chain for underwater geomagnetic navigation. It distinguishes scalar and vector measurements; compares shipborne, towed, and AUV-mounted survey configurations, calibration requirements, platform-interference mitigation, and uncertainty sources; reviews global, regional, and local magnetic models; and evaluates nonlinear map-aided positioning. Existing approaches are organized into map-based matching, filter-aided navigation, geomagnetic simultaneous localization and mapping (SLAM), and matching-area adaptability assessment. Their assumptions, data requirements, uncertainty treatment, accuracy evidence, and computational burden are critically compared. Persistent gaps include magnetic cleanliness, three-dimensional mapping, weak-feature-area observability, benchmark datasets, uncertainty quantification, and reproducible long-duration sea trials. Full article

Bats are one of the most widespread, but also the least researched groups of mammals. Their guano is an important source of DNA because it is often readily available even if bats are not, and it may be used to reliably identify different species of bats. According to the most recent data, there are 31 species of bats recorded in Bosnia and Herzegovina, identified by the morphometric and acoustic methods. This study had the goal of studying bat diversity in Bosnia and Herzegovina by sequencing the COI gene from guano samples and comparing the results with the results of morphometric measurements. A total of 10 bat species were identified through morphometric analysis, while 13 bat species were identified through the sequencing of COI gene from guano samples, including a new species for the country: Rhinolophus mehelyi. Sequencing has increased the number of species recorded on each locality and resolved inconclusive morphological findings except in the case of M. myotis/blythii. The results indicate that the biodiversity of bats in Bosnia and Herzegovina is larger than estimated and that COI sequencing from guano can be used for regular monitoring and for identification of sites of special importance to bats. Full article

The transition from internal combustion engine vehicles to battery electric vehicles has changed the acoustic design problem in automotive engineering. The absence of combustion-related masking increases the perceptibility of tonal and narrowband sources, including gear whine, electric motor orders, inverter-related components, tire cavity resonances, auxiliary system noise, and lightweight-panel radiation. At the same time, mass-based acoustic treatments conflict with electric vehicle lightweighting, range, cost, and sustainability targets. Vibroacoustic metamaterials offer an alternative route by manipulating elastic and acoustic wave propagation through architected geometries, local resonances, periodicity, membranes, lattice architectures, and adaptive or topological wave-control mechanisms. This review examines vibroacoustic metamaterials for low-frequency electric vehicle noise, vibration, and harshness (EV NVH) from an engineering perspective. It covers mechanisms, EV-specific NVH problems, component applications, materials, manufacturing, modeling, validation, AI-assisted design, sustainability, and technology readiness. Particular emphasis is placed on order-targeted, path-oriented, manufacturable, and experimentally validated solutions for electric-drive (e-drive) housings, wheel arches, battery enclosures, body panels, covers, and auxiliary systems. The review concludes that vibroacoustic metamaterials are most promising when integrated into conventional NVH workflows through order analysis, transfer path ranking, robust resonator tuning, durability validation, and multi-objective design optimization. Full article

This paper demonstrates how detailed acoustic micro-segmentation can serve as a vital decision-support tool, providing localized, evidence-based data required to effectively integrate environmental acoustics and foster community co-design in urban rail modernization planning. Furthermore, while physical noise barriers are widely praised as standard mitigation products in transport engineering, our analysis highlights their severe inherent limitations, including spatial constraints, high costs, and visual pollution, making them highly unsuitable for dense historical fabrics. As viable alternatives, we propose the implementation of active, source-targeted engineering technologies (e.g., rail absorbers, modernized track beds) alongside dynamic operational governance. To be effective, these alternative solutions must be sourced and embedded directly into the earliest stages of infrastructural project documentation. Ultimately, this paper demonstrates that evidence-based acoustic governance is an essential institutional pillar for long-term resilience, providing interdisciplinary perspectives that inform future sustainable transport policy and practice. Full article

Background/Objectives: Spatial hearing enables listeners to segregate competing sound sources in complex acoustic environments. Two key components of spatial hearing are localization acuity and spatial release from masking (SRM). Although both rely on similar binaural cue processing, their relationship remains unclear. The present study aimed to investigate localization acuity using frequency-specific and broadband stimuli and to determine how these measures relate to SRM in young normal-hearing listeners. Methods: Forty-five normal-hearing participants completed free-field localization and speech identification tasks using a multi-loudspeaker array. Localization acuity was assessed using one-third octave low-frequency (500 Hz), high-frequency (5000 Hz), and broadband noise stimuli. SRM was measured using a Coordinate Response Measure (CRM) speech task under colocated and spatially separated conditions (±30°). Localization performance was quantified using percent correct and root-mean-square (RMS) error, and relationships between localization acuity and SRM were examined using correlation analyses. Results: Localization performance varied significantly with stimulus bandwidth, with broadband stimuli yielding the highest accuracy, followed by low- and high-frequency conditions. Listeners demonstrated robust SRM (~5.6 dB). Moderate negative correlations were observed between RMS error and SRM across all stimulus conditions. Although the broadband condition yielded numerically larger correlation coefficients, differences among correlations were not statistically significant. Conclusions: Localization acuity was moderately associated with SRM across stimulus conditions. Although numerically larger correlations were observed for broadband stimuli, these differences were not statistically significant. The findings suggest that localization acuity represents one of several factors contributing to spatial hearing performance in complex listening environments. Full article