Search

Tweezers based on optical, electric, magnetic, and acoustic fields have shown great potential for contactless object manipulation. However, current tweezers designed for manipulating millimeter‐sized objects such as droplets, particles, and small animals exhibit limitations in translation resolution, range, and path complexity. Here, a novel acoustic vortex tweezers system is introduced, which leverages a unique airborne acoustic vortex end effector integrated with a three‐degree‐of‐freedom (DoF) linear motion stage, for enabling contactless, multi‐mode, programmable manipulation of millimeter‐sized objects. The acoustic vortex end effector utilizes a cascaded circular acoustic array, which is portable and battery‐powered, to generate an acoustic vortex with a ring‐shaped energy pattern. The vortex applies acoustic radiation forces to trap and spin an object at its center, simultaneously protecting this object by repelling other materials away with its high‐energy ring. Moreover, The vortex tweezers system facilitates contactless, multi‐mode, programmable object surfing, as demonstrated in experiments involving trapping, repelling, and spinning particles, translating particles along complex paths, guiding particles around barriers, translating and rotating droplets containing zebrafish larvae, and merging droplets. With these capabilities, It is anticipated that the tweezers system will become a valuable tool for the automated, contactless handling of droplets, particles, and bio‐samples in biomedical and biochemical research. [ABSTRACT FROM AUTHOR]

In this paper, we further develop a novel, efficient approach to the problem of signal detection against background noise based on a nonlinear residual functional called the neuron-like criterion function (NCF). A detailed comparison of the NCF-based technique and the conventional correlation criterion function (CCF)-based matched-signal detection is performed. For this purpose, we calculated the detection performance curves for both techniques and found the range of the problem parameters in which the NCF-based detector shows a certain advantage. The latter consists of achieving a fixed value of detection probability at a lower threshold value of the input signal-to-noise ratio (SNR) compared to the CCF-based detector. Special attention is given to the practically important scenario of receiving a weak signal against the background of non-stationary noise with a certain trend (positive or negative) of its intensity. For these two specific cases, modified NCFs are given, which are then used for computer simulation. For both broadband and narrow-band signals, the quantitative bounds of the most effective use of the derived NCFs are established and interpreted. The real sea noise data obtained from two underwater acoustic arrays, one stationary on the sea bottom and the other towed near the sea surface, are used for experimental validation. The experimental data processing results confirm the simulation results and make it possible to demonstrate the advantage of the NCF if the noise intensity shows a significant trend over the signal observation interval. The latter case obviously corresponds to the use of the towed array in the coastal area. [ABSTRACT FROM AUTHOR]

The aim of this work is to describe a rich set of acoustic transmission loss observations that were completed in a coastal environment. The data library, enumerated in detail and publicly posted, is comprised of pitch-catch acoustic transmission loss measurements along with concurrent high spatial resolution meteorological observations. The meteorological parameters include near-surface temperature profiles, vertical wind speed profiles in the acoustic propagation direction, and significant wave height estimates. The acoustic source is positioned on an anchored vessel such that the first several hundred meters of the acoustic range is over open water with one microphone array positioned at the shore. A second microphone array is placed several hundred meters inland along the same source-to-receiver heading. The path between the two acoustic arrays is uniform salt marsh vegetation. Observations were made during seven sessions, which represent a variety of atmospheric conditions. That variety of conditions allows for some experimental generalizations about transmission loss as a function of meteorological observations. These include (1) the relationship between vertical effective sound speed profile and transmission loss, and (2) the variability of acoustic pressure with turbulence over time and elevation. [ABSTRACT FROM AUTHOR]

Abstract The performance of Doppler velocity logs (DVLs) in terms of velocity estimate error is directly linked to the geometry of the beam and the pulse transmitted. Beyond a specific transmitted bandwidth, the phase‐shift beamformer can introduce significant errors in velocity estimation. To delineate the operating mechanism of phase‐shift errors within a phased array of acoustic DVLs, the correlation between bottom echo and velocity distribution, in conjunction with the power‐weighted function, was initially examined predicated on spectral estimation theory. Subsequently, numerical and analytical models of the Gaussian‐shaped Doppler spectrum were formulated. The models are employed to evaluate the velocity estimation inaccuracies attributed to phase shifts in extant DVLs, and the comparative results with field experiments corroborate the model's efficacy in forecasting errors. The theoretical findings evaluate the performance limitations of the current phased array transducer design and provide insights for developing new designs. Pool experimental results show that this design effectively reduces the velocity estimation error caused by phase shift under static conditions and in the presence of Doppler frequencies to a level of almost complete elimination of the error compared to conventional configurations.

Acoustic telemetry can provide valuable space-use data for a range of marine species. Yet the deployment of species-specific arrays over vast areas to gather data on highly migratory vertebrates poses formidable challenges, often rendering it impractical. To address this issue, we pioneered the use of acoustic telemetry on basking sharks (Cetorhinus maximus) to test the feasibility of using broadscale, multi-project acoustic receiver arrays to track the movements of this species of high conservation concern through the coastal waters of Ireland, Northern Ireland, and Scotland. Throughout 2021 and 2022, we tagged 35 basking sharks with acoustic transmitters off the west coast of Ireland; 27 of these were detected by 96 receiver stations throughout the study area (n = 9 arrays) with up to 216 detections of an individual shark (mean = 84, s.d. 65). On average, sharks spent ~ 1 day at each acoustic array, with discrete residency periods of up to nine days. Twenty-one sharks were detected at multiple arrays with evidence of inter-annual site fidelity, with the same individuals returning to the same locations in Ireland and Scotland over 2 years. Eight pairs of sharks were detected within 24 h of each other at consecutive arrays, suggesting some level of social coordination and synchronised movement. These findings demonstrate how multi-project acoustic telemetry can support international, cost-effective monitoring of basking sharks and other highly mobile species. Decision support tools such as these can consolidate cross-border management strategies, but to achieve this goal, collaborative efforts across jurisdictions are necessary to establish the required infrastructure and secure ongoing support. [ABSTRACT FROM AUTHOR]

The performance of Doppler velocity logs (DVLs) in terms of velocity estimate error is directly linked to the geometry of the beam and the pulse transmitted. Beyond a specific transmitted bandwidth, the phase‐shift beamformer can introduce significant errors in velocity estimation. To delineate the operating mechanism of phase‐shift errors within a phased array of acoustic DVLs, the correlation between bottom echo and velocity distribution, in conjunction with the power‐weighted function, was initially examined predicated on spectral estimation theory. Subsequently, numerical and analytical models of the Gaussian‐shaped Doppler spectrum were formulated. The models are employed to evaluate the velocity estimation inaccuracies attributed to phase shifts in extant DVLs, and the comparative results with field experiments corroborate the model's efficacy in forecasting errors. The theoretical findings evaluate the performance limitations of the current phased array transducer design and provide insights for developing new designs. Pool experimental results show that this design effectively reduces the velocity estimation error caused by phase shift under static conditions and in the presence of Doppler frequencies to a level of almost complete elimination of the error compared to conventional configurations. [ABSTRACT FROM AUTHOR]

Where's Whaledo is a software toolkit that uses a combination of automated processes and user interfaces to greatly accelerate the process of reconstructing animal tracks from arrays of passive acoustic recording devices. Passive acoustic localization is a non-invasive yet powerful way to contribute to species conservation. By tracking animals through their acoustic signals, important information on diving patterns, movement behavior, habitat use, and feeding dynamics can be obtained. This method is useful for helping to understand habitat use, observe behavioral responses to noise, and develop potential mitigation strategies. Animal tracking using passive acoustic localization requires an acoustic array to detect signals of interest, associate detections on various receivers, and estimate the most likely source location by using the time difference of arrival (TDOA) of sounds on multiple receivers. Where's Whaledo combines data from two small-aperture volumetric arrays and a variable number of individual receivers. In a case study conducted in the Tanner Basin off Southern California, we demonstrate the effectiveness of Where's Whaledo in localizing groups of Ziphius cavirostris. We reconstruct the tracks of six individual animals vocalizing concurrently and identify Ziphius cavirostris tracks despite being obscured by a large pod of vocalizing dolphins. Author summary: Reconstructing the movement of animals from their vocalizations is a powerful method to observe their behavior in situations where visual monitoring is impractical. Arrays of acoustic recording devices can be used to determine the location of vocalizing animals and a series of locations can be linked to form tracks. However, reconstructing tracks requires methods of determining which animal in a group is vocalizing, finding the same vocalization on multiple recording devices, and determining the most likely location of the animal based on the relative times the sound arrived at various recording devices. We have developed a toolkit called Where's Whaledo to assist researchers in reconstructing the behavior of these animals using arrays of acoustic recording devices. This toolkit greatly accelerates the process of reconstructing their tracks using a combination of automated processes and user interfaces. We use Where's Whaledo to reconstruct the tracks of deep-diving beaked whales (Ziphius cavirostris). We successfully reconstruct tracks of groups of up to five whales vocalizing concurrently. [ABSTRACT FROM AUTHOR]

As a practical approach to reflecting the properties of the formation, the slowness of near-wellbore formation is of great significance to geophysical exploration, which can be used to evaluate rock brittleness, wellbore stability, fracturing effect, and invasion depth. Although traditional slowness imaging methods perform well in areas where the thickness of the heterogeneous formation is greater than the length of the receiver array of the logging instrument, they may fail when encountering thin beds. The thin beds' axial thickness, radial invasion depth, and radial slowness are challenging to identify, resulting in obtaining an average slowness value without longitudinal resolution. This paper proposes a thin beds slowness imaging inversion method that can effectively invert the axial thickness, radial invasion thicknesses, and radial slowness variations of thin beds with higher axial resolution compared to traditional methods. The new method adaptively extracts slowness sequences with different radial depths by combining receivers with different source distances. It obtains their corresponding radial thicknesses through ray theory, which does not depend on the arrival times of the first wave. This method is sensitive to thin beds, and the axis thickness of thin beds can be estimated by the change of radial slowness sequence and the combined source distance length. Combining the results at different depths allows a slowness image of the thin beds near-wellbore to be directly obtained. The effectiveness and accuracy of the proposed method are verified by synthetic data and field data. [ABSTRACT FROM AUTHOR]

When the beamforming algorithm is used to locate the fault of the internal structure, the effective fault acoustic signal will be reflected by the structure shell during its transmission process. This results in the microphone signals being polluted, and then the positioning accuracy being low. In this paper, a phase-shifted beamforming algorithm is proposed to segment the microphone signal, extract the time delay of the reflected noise by using the cross correlation property, and then subtract the reflected noise from the raw data to obtain the microphone signal with weakened reflected signal. The newly generated signals are utilized to calculate the cross-spectral matrix of beamforming, which is then used to locate vibration faults. Simulation results show that the phase-shifted beamforming algorithm can more accurately locate the vibration faults of reflective structures. [ABSTRACT FROM AUTHOR]

To solve the problem in target acoustic signal processing and recognition when the target flies at a low altitude based on the acoustic positioning system, which is often affected by external interference and brings false information, this paper proposes a target signal processing and recognition algorithm for low-altitude target acoustic positioning based on variational modal decomposition and the test method of multiple five-element acoustic arrays. This algorithm uses VMD to decompose the target signal into modal components with different central frequencies and then performs wavelet threshold processing on the low-frequency part of the signal. After determining the remaining signal components and the low-frequency part's threshold, the residual component is reconstructed. Based on the test principle and calculation model of the five-element acoustic positioning system, following processing of the low-altitude target acoustic positioning signal using variational modal decomposition, the cross-correlation function method is introduced to perform correlation operations on the basic array of five acoustic sensors and then obtain the time value and time difference of the target acoustic information in each acoustic sensor, ultimately determining the spatial position of the target. Finally, we used the data fusion processing method for target coordinates in multi-acoustic basic arrays to determine the actual target position. By comparing the results obtained using the high-speed camera method with those of the proposed approach, it was found that the average error in the test area of 100 × 100 m was less than 1 m. [ABSTRACT FROM AUTHOR]

The advancement of unmanned platforms is driving the miniaturization and cost reduction of the multi-beam echosounder (MBES). In the process of MBES array calibration, the mutual coupling significantly impacts the performance of parameter estimation. We propose a correction method to mitigate the mutual coupling effects in the calibration of MBES acoustic array. Initially, a near-field focused beamforming model is established to assess the influence of mutual coupling. Subsequently, the covariance matrix in the frequency domain is constructed to enhance algorithm efficiency and simplify solution procedures. This construction eliminates the need for a low-pass filtering step after heterodyning through extracting peak values near zero frequency in the signal frequency domain. Meanwhile, the Toeplitz property is leveraged to render the estimation results independent of the mutual coupling matrix. Finally, the mutual coupling coefficients and the direction of arrival (DOA) are joint-estimated and the Cramér–Rao bound is derived. The presented method effectively addresses the engineering challenge of MBES mutual coupling calibration. Additionally, the performance of the proposed method is verified through the measured data in simulation and tank experiments. [ABSTRACT FROM AUTHOR]

To extract valuable characteristic information from the acoustic radiation signal of rolling bearings, a novel mathematical morphological network (MMNet) is proposed. First, a mathematical morphological network layer is constructed by leveraging the advantages of a multi-scale enhanced top-hat morphological operator (MEAVGH) that can extract positive and negative pulses, which are then integrated into the deep learning network. Second, the input signal undergoes processing with different scale structural elements (SEs) to obtain multi-branch data. This is followed by channel attention and spatial attention mechanism-based weighting of the generated multi-branch data. Finally, the fused information is fed to the neural network to yield the final result. The experimental results demonstrate the efficacy of the proposed method in extracting fault feature information, achieving a fault classification accuracy of 98.56%. Furthermore, the algorithm exhibits robustness and high training efficiency. Comparative analysis reveals that the proposed method outperforms other approaches regarding cluster analysis, accuracy, recall rate, and computational efficiency. These findings further highlight the advantages of MMNet in acoustic signal-based fault diagnosis for rolling bearings. [ABSTRACT FROM AUTHOR]

The fisheries history of the Giant Sea Bass, Stereolepis gigas (Telostei: Polyprionidae), is closely linked to its spatial ecology. Its overharvest is directly associated with formation of spatially distinct spawning aggregations during summer, while its subsequent recovery is hypothesized to be the result of spatially explicit gear restrictions. Understanding the spatial ecology of Giant Sea Bass is a key part of efforts to assess contemporary threats such as commercial harvest and incidental catch by recreational fisheries. In this study, we used acoustic telemetry to characterize Giant Sea Bass space use in the La Jolla kelp forest using an acoustic array that encompasses two marine protected areas (MPAs) and heavily trafficked recreational fishing grounds. Five of the seven fish we tagged remained in the La Jolla array for at least 6 months. Two fish were resident across multiple years, with one fish consistently detected for 4 years. Only one fish was detected in the broader network of regional acoustic receivers, moving north approximately 8 km to Del Mar. Most tagged fish had home ranges and core use areas indicating they spend considerable time outside MPAs, particularly in areas with high recreational fishing activity. During spawning season we detected fish less frequently in the La Jolla array and recorded higher movement rates. While the current MPA network in La Jolla by no means offers complete protection to this fish, it does appear to support long-term persistence of some individuals in a region of exceptionally high recreational fishing pressure. [ABSTRACT FROM AUTHOR]

Abstract Underwater acoustic target detection with multiple autonomous underwater vehicles (AUVs) has the advantage of scalable aperture, however, it depends on the accurate estimation of the shape and structure of the swarm. In this study, a method based on an active sound source is proposed for geometry estimation of distributed nodes. Pulses or chirp signals, transmitted by the source, arrive AUV nodes with different time delays and are collected by the hydrophones, from which the formation geometry could be estimated. Firstly, the frequency‐sliding generalised cross‐correlation (FS‐GCC) feature matrix between the signals received by each node and the reference node is extracted. Secondly, an autoencoder network is employed to enhance the time delay line implied in the FS‐GCC matrix, from which a time delay between two nodes is obtained. A time delay vector could be constructed by concatenating the delays between the reference node and all other nodes when the source lies at different orientations. Lastly, the time delay matrix, which is composed of time delay vectors in a time window when AUV circularly moves around the detection nodes, is further decomposed by singular value decomposition to obtain the formation geometry. The feasibility and effectiveness are verified by the simulation dataset, anechoic pool experiment, and lake trial. The root mean square error of the proposed geometry estimation method drops by 9% and 54% for two typical geometries when compared with ref. [1] for the simulation dataset, which becomes 45% and 37% for the anechoic pool experiment. Though the estimation error increases in lake trials, the proposed method achieved a relatively better precision. It is found that the proposed method has better performance when the formation geometry of AUVs approaches a regular polygon and when the source works in a stop‐and‐go mode. Furthermore, when the source distance meets the far‐field assumption, the azimuthal span of source movement relative to AUVs should be larger than 30°.

The spatial structure of a far-field acoustic wavefield created by a sparse horizontal array of nondirectional emitters is considered. It is shown that the array can selectively excite certain modes of the acoustic wavefield. The number of an excited mode depends on the angle with respect to the array axis. The results of numerical simulation are presented for two models of a waveguide and for an array mounted at the ocean bottom. It is shown that the efficiency of single mode excitation grows with an increase in the modal number. The angular dependence of the excited modal spectrum is studied. It is shown that this dependence consists of several branches corresponding to the most excited modes. [ABSTRACT FROM AUTHOR]

Recent developments have shown that spatial structures devised from origami or low-dimensional rigid linkage mechanisms can be used to construct deployable arrays for antennas or satellites. Yet, some of these structures are limited to deployment in fixed planes or directions, or do not define straightforward processes for deployment. To surmount these limitations, this research introduces a reconfigurable single-degree-of-freedom spatial structure devised from a Kresling-inspired mechanism with integrated scissor arms. Analytical models are constructed to demonstrate compaction, deployment, and acoustic wave guiding capabilities of the proposed, modular structure. The influences of the geometric parameters on compaction, deployment, and scissor arm orientation are also explored, and reveal modular scissor arm behavior and large deployment-to-compaction area ratios. The acoustic wave guiding capabilities of the Kresling-inspired scissor structure are exemplified via a structure using spiral scissor arms, thereby proposing a novel concept for the construction of deployable wave guiding arrays. Experimental studies with model arrays complement the analytical findings of both the geometric reconfigurations and wave guiding functionality. Finally, out-of-plane configurations are depicted to demonstrate the three-dimensional shape change capabilities of the Kresling-inspired scissor structure. The results in this study encourage broader exploration of the interfaces between origami inspired structures and rigid linkage mechanisms. [ABSTRACT FROM AUTHOR]

Detection and identification of species, subspecies or stocks of whales, dolphins and porpoises at sea remain challenging, particularly for cryptic or elusive species like beaked whales (Family: Ziphiidae). Here we investigated the potential for using an acoustically assisted sampling design to collect environmental (e)DNA from beaked whales on the U.S. Navy's Atlantic Undersea Test and Evaluation Center (AUTEC) in The Bahamas. During 12 days of August 2019, we conducted 9 small-boat surveys and collected 56 samples of seawater (paired subsamples of 1L each, including controls) using both a spatial collection design in the absence of visual confirmation of whales, and a serial collection design in the proximity of whales at the surface. There were 7 sightings of whales, including 11 Blainville's beaked whales (Mesoplodon densirostris). All whales were located initially with the assistance of information from a bottom-mounted acoustic array available on the AUTEC range. Quantification by droplet digital (dd)PCR from the four spatial design collections showed no samples of eDNA above the threshold of detection and none of these 20 samples yielded amplicons for conventional or next-generation sequencing. Quantification of the 31 samples from four serial collections identified 11 likely positive detections. eDNA barcoding by conventional sequencing and eDNA metabarcoding by next-generation sequencing confirmed species identification for 9 samples from three of the four serial collections. We further resolved five intra-specific variants (i.e., haplotypes), two of which showed an exact match to previously published haplotypes and three that have not been reported previously to the international repository, GenBank. A minimum spanning network of the five eDNA haplotypes, with all other published haplotypes of Blainville's beaked whales, suggested the potential for further resolution of differences between oceanic populations. [ABSTRACT FROM AUTHOR]

To solve the synthesised accuracy degradation of traditional Bayesian compressive sensing (BCS) in wideband multi‐beam hydrophone array synthesis, a novel sparse array synthesis method based on block‐structure Bayesian compressive sensing (BS‐BCS) is proposed for frequency‐invariant and multi‐angle beampatterns. The multi‐angle beampatterns at different frequencies are synthesised in block structure using the shared position strategy which effectively reduces the number of array elements. In order to meet the minimum spacing requirement of adjacent array elements in practical engineering, the constraint converted off‐grid method is proposed to improve the array synthesis accuracy. The grid scaling is introduced to obtain the possible array element positions. The array positions and weights can be solved by the BCS solver and corrected by Taylor perturbation. To validate the effectiveness and feasibility of the proposed method, simulations and actual experiments are carried out. The synthesised errors and peak sidelobe levels (PSLLs) of multi‐angle beampatterns obtained by the constraint converted off‐grid method outperforms those of other methods. The beamforming results of actual experiments in marine environment show that the PSLLs of the beampatterns obtained by BS‐BCS is lower at least 6.3 dB than that of uniform array, which demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A metal diaphragm-based omnidirectional fiber-optic acoustic sensor with high sensitivity has been developed in this work. The acousto-optic transducer of the sensor is a single-wavelength extrinsic Fabry–Pérot interferometer (EFPI) that is highly sensitive to the displacement of the diaphragm's center. The sensor can stably work in the linear response region of the EFPI in a wide range of temperature from −20 to 60 °C. The pressure sensitivity of the sensor is larger than 800 mV/Pa, and the sensitivity fluctuation in the frequency range from 100 Hz to 6 kHz is smaller than 3 dB. The noise-limited minimum detectable pressure obtained at 1 kHz of the sensor is 126 μPa/Hz1/2. In addition, the above-prepared fiber-optic acoustic sensors present excellent phase consistency with each other, which facilitates the formation of a sensor array for sound source localization. In this work, a cross-shaped fiber-optic sensor array was prepared and then used to detect and track a small drone flying in the field. The experimental results show that the sensor array can capture the acoustic fingerprint of the drone at a distance as far as 300 m. This detection distance is more than ten times longer than that of a conventional electret condenser microphone. The azimuth angle of the drone obtained with the fiber-optic acoustic sensor array has a deviation of smaller than 10° relative to the GPS data from the drone. [ABSTRACT FROM AUTHOR]

The ability to create directional sound beams is fundamental to acoustic sensing. Traditionally, acoustic beams are most commonly produced by phased arrays, which increase the cost and complexity of the systems in which they are implemented. Phononic structures have theoretically been shown to possess Dirac cones that can be manipulated to produce angular collimated beams. Dirac cones are usually encountered in phononic crystals with inclusions significantly more compressible than the surrounding media, e.g., rubber inclusions in a water medium, a characteristic not easily realized in air. In addition, there are no effective and practical means to tune phononic structures that can achieve a broad range of Dirac point manipulation, which is essential to changing the direction and focus of acoustic beams. To advance the state of the art, this research proposes a novel approach to produce steerable collimated beams in air by harnessing reconfigurable origami phononic structures with adjustable metamaterial inclusions. The proposed structure is shown to produce dramatic lattice reconfiguration and control of Dirac points in a broad range, and thus achieve collimated beams with on-demand tunable frequency and angle. These advancements provide a simple, cost-effective alternative to acoustic phased arrays, greatly expanding the potential of acoustic sensing. [ABSTRACT FROM AUTHOR]

This work concerns the development and testing of a setup that uses laser-induced ultrasound sources to achieve synthetic transmit aperture ultrasound imaging. The sources are created by sequentially firing 32 contiguous multi-mode optical fibers to illuminate an optically absorbing film with nanosecond-pulsed laser light. Ultrasound is generated by the photoacoustic effect and insonifies the sample under investigation. Ultrasound that has interacted with the sample is detected in reflection mode using a conventional ultrasound transducer array. We present a custom-developed optical fiber multiplexing setup that enables sequential firing of the optical fiber array and characterize the acoustic fields produced by the laser-induced approach using hydrophone measurements. The integrated setup is used to make images of wire phantoms. Following this, images are taken of a breast-mimicking phantom as well as the wrist of one of the authors. Imaging results from the new approach and from conventional ultrasound imaging are compared. The lateral and axial point-spread function values show broad agreement between the two approaches, whereas the phantom and in vivo images exhibit some differences in contrast values. This work is, to our knowledge, the first instance of laser-induced ultrasound synthetic transmit aperture imaging using a clinical ultrasound array. [ABSTRACT FROM AUTHOR]

We propose a phenomenological model, built from results obtained by finite-element numerical simulations, for the transmission and reflection of acoustic waves by a two-dimensional array of cylindrical cavities in a soft elastic medium. We show that the acoustic properties of a cylindrical cavity can be described by two geometrical parameters: its aspect ratio (AR) and the radius of the sphere of equivalent volume. Cylinders with AR close to one are acoustically similar to spheres, whereas flat cylinders exhibit a lower resonance frequency and an increased damping due to their ability to emit shear waves. We provide an example of how our new phenomenological analytical model can help to design thin coatings that can turn strong acoustic reflectors into good absorbers. [ABSTRACT FROM AUTHOR]

Currently, phased arrays are increasingly used in ultrasonic nondestructive testing. One of the most important parameters of ultrasonic nondestructive testing with the application of phased arrays is the angular resolution. This paper presents the results of studies of the angular resolution of concave and convex acoustic arrays in ultrasonic testing with the application of the total focusing method. Computer modeling of concave and convex acoustic arrays consisting of 16, 32 and 64 elements with distances between elements of 0.5 and 1 mm and arc radii of 30 and 60 mm have been performed. The results obtained by computer modeling were confirmed via in situ experiments. [ABSTRACT FROM AUTHOR]

For improving performance of the towed array sonar during the manoeuvring period, a processing framework is proposed based on joint estimation of direction of arrival (DOA) and the array shape. The sparse Bayesian learning (SBL) algorithm is utilised to accurately estimate the DOAs of interesting targets. Meanwhile, the towed array shape is modelled as a parabola array, and the array element positions are estimated using the bow of the parabola. Then, an approximate posterior covariance is implemented to the SBL for a fast converging speed required by practical applications. Besides, the co‐prime array structure is considered for the uniform linear array to further reduce the computational load. The numerical simulations have verified the effectiveness of the fast converging SBL method. MAPEX2000 experimental data processing results have shown that the proposed framework performs well in detection of weak targets during slow turns. [ABSTRACT FROM AUTHOR]

In the article, the study of the quality of tomogram focusing during the inspection of objects with curved surfaces by flexible acoustic array was described. The main goal of the study was theoretically and experimentally define the acceptable deviation limits of the elements' coordinates values. The tomogram reconstruction was performed by the total focusing method. The Strehl ratio was chosen as a criterion for assessing the quality of tomogram focusing. The ultrasonic inspection procedure were simulated and validated experimentally by means of convex and concave curved arrays. In the study, it was proven that the elements coordinates of the flexible acoustic array were determined with an error of no more than 0.18λ and the tomogram image was obtained in sharp focus. [ABSTRACT FROM AUTHOR]

The diversity combining technique performs well in the inhibition of multipath, it has been widely used in underwater acoustic (UWA) array signal processing. However, the underwater noise can seriously affect the processing results of the diversity. The conventional filtering algorithms cannot deal with the nonlinear components of underwater radiation noise and have a poor processing effect on complex signals. This study proposes a novel underwater array angle diversity method based on a two-stage model to overcome the problem. A noise-reduction model with a deep convolutional neural network (DCNN) as the backbone network for deep residual learning by preprocessing complex-type data on the received and reference noise signals in the first stage. In the second stage, a modified weighted delay summation beamformer group model is constructed. This model adjusts the weights of each channel by a gradient descent criterion. The desired angle estimates and delay information are then obtained. Finally, the delayed combining of the signals of each path is completed by the combining strategy. Simulation test results show that the proposed algorithm has a lower bit error rate (BER) for diverse received signals. On-lake tests further verify the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

The presented work aims to adapt a Geiger‐based method and localize pendulum impacts applied on a rigid steel plate using the data set of a 112 microphone array. The advantage compared to measurements with piezoelectric sensors, where normally a number of sensors are involved, is the superior number of microphones. To solve the Geiger algorithm on the three‐dimensional domain, at least data from three sensors and the primary wave velocity are required (four equations). Moreover, if the system of equations is overdetermined, an error minimization can be performed, for example, with the least‐squares method. Since in this work the distance between array and plate is constant, the algorithm can be even reduced to a two‐dimensional problem (only three equations required). Indeed, the superior overdetermination of 112 microphone data allows to index the optimal data set by combing microphone data and thus achieve the best localization results for the optimal microphone. This study is relevant to the scientific community because it will allow uncontrolled events cracks or other damage to be localized with a great accuracy and reliability. [ABSTRACT FROM AUTHOR]

Underwater acoustic target detection with multiple autonomous underwater vehicles (AUVs) has the advantage of scalable aperture, however, it depends on the accurate estimation of the shape and structure of the swarm. In this study, a method based on an active sound source is proposed for geometry estimation of distributed nodes. Pulses or chirp signals, transmitted by the source, arrive AUV nodes with different time delays and are collected by the hydrophones, from which the formation geometry could be estimated. Firstly, the frequency‐sliding generalised cross‐correlation (FS‐GCC) feature matrix between the signals received by each node and the reference node is extracted. Secondly, an autoencoder network is employed to enhance the time delay line implied in the FS‐GCC matrix, from which a time delay between two nodes is obtained. A time delay vector could be constructed by concatenating the delays between the reference node and all other nodes when the source lies at different orientations. Lastly, the time delay matrix, which is composed of time delay vectors in a time window when AUV circularly moves around the detection nodes, is further decomposed by singular value decomposition to obtain the formation geometry. The feasibility and effectiveness are verified by the simulation dataset, anechoic pool experiment, and lake trial. The root mean square error of the proposed geometry estimation method drops by 9% and 54% for two typical geometries when compared with ref. [1] for the simulation dataset, which becomes 45% and 37% for the anechoic pool experiment. Though the estimation error increases in lake trials, the proposed method achieved a relatively better precision. It is found that the proposed method has better performance when the formation geometry of AUVs approaches a regular polygon and when the source works in a stop‐and‐go mode. Furthermore, when the source distance meets the far‐field assumption, the azimuthal span of source movement relative to AUVs should be larger than 30°. [ABSTRACT FROM AUTHOR]

The detection and localization of acoustic sources remain technological challenges in bioacoustics, in particular, the tracking of moving underwater sound sources with a portable waterproof tool. For instance, this type of tool is important to describe the behavior of cetaceans within social groups. To contribute to this issue, an original innovative autonomous device, called a CETOSCOPE©, was designed by ABYSS NGO, including a 360° video camera and a passive acoustic array with 4 synchronized hydrophones. Firstly, different 3D structures were built and tested to select the best architecture to minimize the errors of the localizations. Secondly, a specific software was developed to analyze the recorded data and to link them to the acoustic underwater sources. The 3D localization of the sound sources is based on time difference of arrival processing. Following successful simulations on a computer, this device was tested in a pool to assess its efficiency. The final objective is to use this device routinely in underwater visual and acoustic observations of cetaceans. [ABSTRACT FROM AUTHOR]

A three-microphone acoustic array (OSU1), with microphones that have a flat response from 0.1 to 200 Hz, was deployed for 6 years (2016–2022) at Oklahoma State University (OSU) in Stillwater, Oklahoma, and sampled at 1000 Hz. This study presents a new dataset of acoustic measurements in a high interest region (e.g., study of tornado infrasound), provides a broad overview of acoustic detections and the means to identify them, and provides access to these recordings to the broader scientific community. A wide variety of infrasound and low-audible sources were identified and characterized via analysis of time traces, power spectral densities, spectrograms, and beamforming. Low, median, and high noise models were compared with global noise models. Detected sources investigated include natural (microbaroms, bolides, earthquakes, and tornadoes) and anthropomorphic (fireworks, airplanes, and munition detonations) phenomena. Microbarom detections showed consistency with literature (~0.2 Hz with peak amplitude in the winter) and evidence that the frequency was inversely related to the amplitude. Fireworks and airplanes served as verified local events for the evaluation of data quality and processing procedures. Infrasound from munition detonations, that occur nearly daily at a location 180 km southeast of OSU1, matched the available ground truth on days with favorable propagation to OSU1. A clear bolide detection with an estimated position of approximately 300 km from OSU1 was shown. Most detected earthquakes were seismic arrivals due to sensor vibrations; however, the largest earthquake in Oklahoma history showed an acoustic arrival. Finally, data from multiple tornadoes are discussed, including a previously unpublished quasi-linear convective system tornado. [ABSTRACT FROM AUTHOR]

This work examines the use of generative adversarial networks for reconstructing sound fields from experimental data. It is investigated whether generative models, which learn the underlying statistics of a given signal or process, can improve the spatio-temporal reconstruction of a sound field by extending its bandwidth. The problem is significant as acoustic array processing is naturally band limited by the spatial sampling of the sound field (due to the difficulty to satisfy the Nyquist criterion in space domain at high frequencies). In this study, the reconstruction of spatial room impulse responses in a conventional room is tested based on three different generative adversarial models. The results indicate that the models can improve the reconstruction, mostly by recovering some of the sound field energy that would otherwise be lost at high frequencies. There is an encouraging outlook in the use of statistical learning models to overcome the bandwidth limitations of acoustic sensor arrays. The approach can be of interest in other areas, such as computational acoustics, to alleviate the classical computational burden at high frequencies. [ABSTRACT FROM AUTHOR]

An eigenstructure analysis is used to identify anomalies in large acoustic array measurements of airfoil trailing edge noise. Cross-spectra of 102 microphones distributed in a spiral configuration were inspected considering a range of inflow conditions and airfoil configurations. A measurement expectation is set by repeat measurements of non-anomalous data and is used for the analysis of additional data. This method is based solely on the comparison between the eigenstructure of cross-spectral matrices and can be used to efficiently inspect data for anomalies without having to beamform, as is conventional. Thus, processing and reviewing beamform maps can be relegated to post-processing after the experiment when more time is available. [ABSTRACT FROM AUTHOR]

Abstract A method based on beam tracking in an underwater acoustic (UWA) time‐varying channel was proposed to improve the performance of UWA spread spectrum communication systems using arrays. In the ocean, the acoustic signal reaches the receiver through various paths, and the signal on each path has its own propagation delay and incidence angle. To effectively use the time and space characteristics of the received signal in a typical time‐varying or all types of UWA channels of mobile communication scenarios, the multiple signal classification (MUSIC) algorithm constantly updates the beam orientation. In addition, the receiving signal beamforming and maximum ratio combination can solve the severe inter‐symbol interference in a sea channel and significantly improve the signal‐to‐noise ratio of the received signal; the UWA spread spectrum communication system is more reliable. Through computer simulation and an actual pool experiment, a space–time receiver for an UWA spread spectrum communication system with beam tracking was successfully implemented.

Marine organisms inhabiting coastal waters are known to be driven by periodic cycles such as diel, tidal, and seasonal changes. Humpback whales (Megaptera novaeangliae) breed in shallow and warm coastal waters, with males singing complex songs during the breeding season. To investigate periodic variations in humpback whale singing activities, we conducted fixed passive acoustic monitoring in the Ogasawara (Bonin) Islands, Japan, from winter to spring during 2016–2018. The singing activity and individual number of singers were observed throughout the day and night using a very long baseline passive acoustic array. The occurrence of singers peaked before sunrise and in the evening and was reduced during the daytime. The frequency of song reception depended on the tidal phase. A generalised additive model demonstrated that the occurrence of singers increased during the flood tide and decreased during the ebb tide in the waters west of Chichijima Island. These results suggest that the singing behaviour of humpback whales in breeding areas is affected by the diel and tidal cycles. Male humpback whales may change their behaviour or singing location depending on the strength and direction of the tidal current, considering that the selection of a stable location is beneficial for singing whales. [ABSTRACT FROM AUTHOR]

When an optimization approach is taken for ultrasonic array design, the relationship between imaging performance and acoustic beam characteristics (ABCs) needs to be considered. A general optimization approach for ultrasonic array design is proposed based on principal component regression (PCR), which is used to establish the relationship between imaging performance indicators (IPIs) and ABC. A linear and a circular ultrasonic array design scenarios are simulated to demonstrate the effectiveness of the proposed approach. A set of beam and reflector response simulations are implemented to collect beam characteristics and IPIs, an explicit mapping function between which is built by PCR. Then, the mapping function is applied as an objective function to form an optimization model. The global optimization algorithm is used to locate the optimal solution of array parameters and setup. Simulation results demonstrate that the acoustic beam and imaging performance are associated quantitatively by PCR mapping, making the relationship explicitly interpretable, that the beam and imaging can be optimized simultaneously, and that acoustic response modeling may be skipped during iterative optimization, speeding up the approach. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sparse representation beamformer for robotic condition localization in a pipe. • Direction identification of echoes with plane wave and higher-order modes in a pipe. • Differentiation of blockage and lateral using beamforming. • Cancellation of blind zone from the reverberation in manholes. • A robust acoustic algorithm to identify the length of the pipe. Pipe inspection robots with sensors significantly enhance the maintenance of water systems by enabling early defect detection and reducing the risks of leaks and environmental damage. This paper introduces a sparse representation acoustic beamformer designed to locate artefacts within pipes using a short linear microphone array on a robot. The primary contributions include: (i) a new acoustic beamforming approach based on sparse representation that accurately predicts pipe conditions with a localization error within 3 % of the sensing distance; (ii) an enhanced beamforming algorithm combining plane wave and first non-axisymmetric mode, extending the frequency range from < 1300 Hz to < 2200 Hz in a 150 mm diameter pipe (an increase by 1.69 times), effectively managing unwanted acoustic reverberations and distinguishing blockages from lateral connections; and (iii) a novel robust algorithm predicting pipe length with an error margin within 2 %. This research advances acoustic sensing technologies for autonomous mobile robots inspecting buried pipes. [ABSTRACT FROM AUTHOR]

Automatic pedestrian detection in a vehicle is of vital importance in Advanced Driver Assistance Systems (ADAS). Sensors currently used are based on cameras, radars and lidars, whose performance is degraded in environments with reduced visibility: night, smoke, fog, etc. This paper has validated the use of an active array of 150 MEMS (Micro-Electro Mechanical Systems) microphones incorporated into a conventional car moving in real urban traffic conditions, with the system working in real time, at a rate of 8 detections per second. Together with beamforming, Constant False Alarm Rate (CFAR) detection and lane detection algorithms, a crucial algorithm has been incorporated for the proper performance of the system that discriminates the detections of objects or pedestrians generated by the system from the false alarms generated by road imperfections, such as bumps, cracks, etc. Based on 6000 captures, performed with the car moving at 30 km/h, which is the typical speed limit in urban environments, it has been possible to detect pedestrians positioned at a distance from the car varying between 5 and 20 m, with a detection probability of 0.91 and a false alarm probability of 0.01. The results obtained have validated the effectiveness of using active acoustic arrays in the field of pedestrian detection and position estimation from moving cars in urban environments. The fusion of the presented system with the systems currently used for this purpose, would significantly improve the performance of pedestrian detection systems interacting with AEB (Automatic Emergency Breaking) systems, extending their operability to environments with reduced visibility, and resulting in the reduction in the number of possible collisions with pedestrians, thus increasing their safety. [Display omitted] • Automotive and transportation industries try to reduce traffic accidents involving pedestrians. • Acoustic system based on a low-cost MEMS microphone array. • This system can be used to detect and estimate the position of a person. • This system performs properly mounted on a vehicle moving in urban environments. • This system improves the performance of pedestrian detection in reduced visibility environments. [ABSTRACT FROM AUTHOR]

• A phononic crystal resonator (PnCR) is proposed for directional enhancement of gear weak fault detection. • The PnCR offers a tunable acoustic gain resonance band to enhance the target weak acoustic signal. • The PnCR demonstrates high acoustic angle resolution with directional enhanced perception enabled. • Experimental results and comparisons highlight its excellent performance for weak fault detection under high energy spatial noise interference. Condition monitoring and diagnosis of the gears is essential to ensure the reliability of the whole mechanical equipment. Sensing technology based on acoustic signals plays a vital role in gear fault diagnosis with its advantages of non-contact and flexible installation. However, the signals detected by acoustic sensing are interfered by spatial noise from the operating environment and other equipment. This interference hampers the detection of weak fault features in gears, thereby limiting the applicability of acoustic sensing technology for fault diagnosis. In this study, combining the great advantages of acoustic wave manipulation and modulation by phononic crystals (PnC) and acoustic metamaterials, a phononic crystal resonator (PnCR) with the ability of directional enhancement of acoustic signals is proposed for fault detection in gears. In contrast to traditional acoustic diagnostic techniques, this method can enhance gear fault features in the desired direction at the front end of the sensing layer while simultaneously suppressing noise from other directions, eliminating the need for large-sized acoustic array systems and complex post-processing algorithms. The effectiveness of the designed PnCR directional acoustic enhancement is explored through numerical simulation and experimental validation. In addition, compared to the conventional resonance demodulation method based on spectral kurtosis, the device exhibits more excellent gear fault orientation enhancement performance at low signal-to-noise ratios (SNR). This work provides new ideas for the development of acoustic sensing with both high sensitivity and high directivity, which has a broad potential for application in the field of mechanical equipment fault diagnosis. [Display omitted] [ABSTRACT FROM AUTHOR]

The supply chain risk of rare-earth permanent magnets has yielded research efforts to improve both materials and magnetic circuits. While a number of magnet optimization techniques exist, literature has not incorporated the permanent magnet failure process stemming from finite coercivity. To address this, a mixed-integer topology optimization is formulated to maximize the flux density of a segmented Halbach cylinder while avoiding permanent demagnetization. The numerical framework is used to assess the efficacy of low-cost (rare-earth-free ferrite C9), medium-cost (rare-earth-free MnBi), and higher-cost (Dy-free NdFeB) permanent magnet materials. Novel magnet designs are generated that produce flux densities 70% greater than the segmented Halbach array, albeit with increased magnet mass. Three optimization formulations are then explored using ferrite C9 that demonstrates the trade-off between manufacturability and design sophistication, generating flux densities in the range of 0.366–0.483 T. [ABSTRACT FROM AUTHOR]

Simple Summary: Shark hazard mitigation measures are often introduced after human-shark interactions, which are increasing. Such measures are often contentious, and care is needed to reduce the risk to ocean users without causing negative ecosystem impacts. Here, we examined the effectiveness of Shark-Management-Alert-in-Real-Time (SMART) drumlines to catch, tag, relocate and release white sharks (Carcharodon carcharias) in the Capes region of Western Australia. The project aimed to examine the movement patterns of white sharks' post-release to determine whether their relocation provided a reduction in risk for ocean users. The effectiveness of the program was also evaluated in terms of minimising the mortality of all animals caught. In total, 352 fish were caught over the 27-month trial period and 91% of animals were released alive in good condition. Only two white sharks (target species) were caught, both of which moved immediately offshore after capture and remained predominantly in offshore waters for the duration of tag deployment. The detection of 24 other tagged white sharks within the acoustic array during the trial period confirms that the target species were not always amenable to capture. Our results reiterate there is no simple remedy for dealing with the complexities of shark hazards and reinforce the importance of trialing mitigation measures under local conditions. The management of human-shark interactions can benefit from the implementation of effective shark hazard mitigation measures. A Shark-Management-Alert-in-Real-Time (SMART) drumline trial in the Capes region of Western Australia was instigated after several serious incidents involving surfers and white sharks (Carcharodon carcharias). The project aimed to determine whether white sharks (target species), which were relocated after capture, remained offshore using satellite and acoustic tagging. Over a 27-month period, 352 fish were caught, 55% of which comprised tiger sharks (Galeocerdo cuvier). Ninety-one percent of animals were released alive in good condition. Only two white sharks were caught; both were relocated ≥ 1 km offshore before release and moved immediately further offshore after capture, remaining predominately in offshore waters for the duration of their 54-day and 186-day tag deployments. Our results confirm that desirable animal welfare outcomes can be achieved using SMART drumlines when response times are minimised. The low target catches and the detection of 24 other tagged white sharks within the study area supported the decision to cease the trial. Our results reiterate there is no simple remedy for dealing with the complexities of shark hazards and reinforce the importance of trialing mitigation measures under local conditions. [ABSTRACT FROM AUTHOR]

Fluid flows generate an acoustic noise field. In principle, oceanic flows on varying time and length scales produce a sound field and its detectability is considered here. A fragile lower bound analysis is made of the acoustic signature, using the Lighthill theory, of a simple train of boundary vortices generated by baroclinic tidal flows. Subject to numerous assumptions, the accompanying sound should be detectable within the hum band of seismo-acoustic pressure fields, and more generally, across the entire oceanic spectrum—likely through wave number analyses of spatially coherent acoustic array data. [ABSTRACT FROM AUTHOR]