Acoustic Technology Research Articles

Method for rock fracture prediction and early warning: Insight from fusion of multi-physics field information

Understanding the precursors leading to rock fracture is crucial for ensuring safety in mining and geotechnical engineering projects. To effectively discern these precursors, a collaborative monitoring approach that integrates multiple sources of information is imperative. This paper considered a rock multi-parameter monitoring loading system, incorporating infrared radiation and acoustic emission monitoring technologies to simultaneously track the rock fracture process. The study delves into the spatiotemporal evolution patterns of infrared radiation and acoustic emission in rock under loading. Utilizing stress, cumulative acoustic emission count, and average infrared radiation temperature (AIRT), the paper establishes a comprehensive evaluation model termed “acoustic-thermal-stress” fusion information, employing principal component analysis (PCA). The research reveals that the sensitivity to rock sample damage response follows the sequence of cumulative acoustic emission count, AIRT, and stress. Furthermore, a novel method for identifying rock fracture precursors is proposed, based on the first derivative of the comprehensive evaluation model. This method addresses the limitations of single physical field information, enhancing the robustness of monitoring data. It determines the average stress level of fracture precursors to be 0.77σmax. Subsequently, the study defines the probability function of rock damage during loading and fracture, enabling the realization of probability-based warnings for rock fracture. This approach introduces a new perspective on rock fracture prediction, significantly contributing to safety monitoring and warning systems in mine safety and geotechnical engineering. The findings of this research hold paramount engineering significance, offering valuable insights for enhancing safety measures in such projects.

Improving non-destructive testing methods for detecting cavity damage and internal defects in stone cultural relics: A focus on ultrasonic testing and acoustic tapping technology

This study employs advanced ultrasonic tomography and Grasshopper software to investigate the internal anomalies within stone materials. We aim to enhance the non-destructive testing (NDT) methods with potential applications extending to modern architecture and stone engineering. Cavity damage and internal defects threaten the structural stability of stone cultural relics. Traditional non-destructive testing methods, while practical, have limitations in assessing these relics comprehensively. This paper proposes an enhanced ultrasonic testing method based on mathematical analysis to accurately detect cavity damage in stone cultural relics. We also investigate imaging techniques for internal defects, combining ultrasonic testing with Grasshopper software for efficient and accurate defect characterization. Additionally, we introduce an acoustic tapping method for detecting internal defects in ancient building stones. Verified through field tests and data analysis, this method is non-invasive, accurate, and fast. The process of detecting stone defects using this technology, along with data analysis methods, experimental results, and application effects, are detailed. This research contributes to the improved preservation and restoration of ancient buildings and extends to other fields, such as modern architecture and stone engineering, highlighting its significance in cultural heritage conservation.

Characterizing behavioral responses of Pacific cod to bottom trawl vessels and gear using archival tag accelerometer data

Fish behavior during the capture process affects the overall efficiency of survey vessels and gear, influencing selectivity and catchability, which in turn influences stock assessments. The effects of behavior on capture are typically investigated through experiments that use video or acoustic technologies to observe behavioral responses of fish to vessels and gear directly. While these approaches provide valuable information about fish behavior, their use is limited to observing the movement of fish inside a small observed area. In this proof-of-concept study, we demonstrate a novel application of bio-logging Pop-up Satellite Archival Tags (PSATs) equipped with accelerometer sensors to observe behavioral responses of free-swimming demersal fish to approaching bottom trawl fishing vessels and gear. By combining PSAT and fishing vessel geolocation data from the Vessel Monitoring System, we characterized diving and herding responses of three individual Pacific cod (Gadus macrocephalus) at-liberty for 21–106 days to trawling fishing vessels. We found that fish descended as trawlers approached, presumably in response to noise generated by the fishing vessel and gear, which supports the previously untested hypothesis that Pacific cod dive in response to approaching fishing vessels and gear, similar to closely related gadids. Additionally, one 88 cm fish swam ahead of a trawl towed at 1.25 m·s−1 (i.e., 1.42 body lengths per second) for 55.6 minutes, covering a distance of 4.17 km before capture, which challenges previous assertions that Pacific cod are unlikely to outswim bottom trawl gear towed at typical towing speeds. This study demonstrates that opportunistically collected archival tag data can be used to improve knowledge of behavioral interactions between fish and fishing gear.

The architecture design checklist of classrooms for children with cochlear implant in rehabilitation centers

Children with cochlear implants (CI) have unique physical, psychological, and behavioral needs compared to typically developing children, thus they go through a rehabilitation process for education and activity purposes in a rehabilitation center (RC). The provision of specialized support for children with CI reflects a nation's commitment to inclusivity and care for all segments of society. This study investigates the research gab of the needs of children with CI (aged 1–6) to identify the fundamental design requirements in order to develop an architectural design checklist for their classrooms. Through literature review and comparisons with standard preschool designs for typically developed children, the research identifies key design elements affecting these children's learning and integration. This study establishes a framework for optimizing RC's classroom design for children with CI. Following a methodological discussion addressing pertinent research considerations, a comprehensive user experience questionnaire was conducted. The questionnaire included participants from various stakeholder groups: parents, educators, medical professionals (psychiatrists and doctors), and design experts (architectural and acoustic engineers). The findings inform the identification of essential design elements encompassing layout, materials selection, ventilation strategies, lighting systems, acoustic control measures, and color palettes. Following analysis, the research concludes with a design checklist outlining optimal ranges (100 % = sub-optimum, 50 % = optimum, 0 % = over design) for each element, including furniture layout, color schemes, materials, classroom shape, lighting, and ventilation. This checklist ensures RC classrooms effectively cater to the specific needs of children with CI.

Channel Prediction for Underwater Acoustic Communication: A Review and Performance Evaluation of Algorithms

Underwater acoustic (UWA) channel prediction technology, as an important topic in UWA communication, has played an important role in UWA adaptive communication network and underwater target perception. Although many significant advancements have been achieved in underwater acoustic channel prediction over the years, a comprehensive summary and introduction is still lacking. As the first comprehensive overview of UWA channel prediction, this paper introduces past works and algorithm implementation methods of channel prediction from the perspective of linear, kernel-based, and deep learning approaches. Importantly, based on available at-sea experiment datasets, this paper compares the performance of current primary UWA channel prediction algorithms under a unified system framework, providing researchers with a comprehensive and objective understanding of UWA channel prediction. Finally, it discusses the directions and challenges for future research. The survey finds that linear prediction algorithms are the most widely applied, and deep learning, as the most advanced type of algorithm, has moved this field into a new stage. The experimental results show that the linear algorithms have the lowest computational complexity, and when the training samples are sufficient, deep learning algorithms have the best prediction performance.

Enhancing acoustic levitation capacity through array geometry optimization

The contactless micromanipulation capability and microgravity environment provided by the acoustic levitation technology have excellent application prospects in many fields, such as droplet dynamics, solidification state physics, life sciences, etc. However, the applications are severely constrained by the limitation of the transducer power. In this paper, we explore an array geometry optimization framework to improve the levitation capability. First, the acoustic pressure attenuation and directional characteristics of commercial transducers are analyzed to uncover the mechanism of the array geometry affecting the acoustic radiation force (ARF). Second, based on the Gor'kov potential theory, the array geometry form of N-elements is derived, and the arrangement in the spherical ring (ASR) method is proposed to obtain the element coordinates. Then, spherical radius and array height are adjusted to obtain the optimal array geometry. On this basis, the directional angle of each transducer is further optimized. Finally, simulation and physical verification are carried out. The simulation results indicate that the ARF increases and then decreases with the spherical radius and array height, which are the existing maximum values. Directional angle optimization (DAO) can improve the ARF, particularly when the array height exceeds the sphere diameter. These findings are consistent with the analytical results. Notably, we built a prototype physical system, and the physical experiments showed that the optimized array improved the axial ARF by 201.2% and the radial ARF by 115.9% over the conventional array. The works presented in this paper offer a valuable design approach for acoustic levitation arrays, thereby contributing to the advancement and application of ultrasonic array levitation technology.

Depth Accurate Prediction and Kerf Quality Improvement of CFRP Through-Hole Laser Cutting via Acoustic Emission Nondestructive Monitoring Technology

Depth Accurate Prediction and Kerf Quality Improvement of CFRP Through-Hole Laser Cutting via Acoustic Emission Nondestructive Monitoring Technology

Analyzing the impact of flexible shells and sound absorbent lining on acoustic wave behavior in ducts

This study focuses on investigating the propagation of acoustic waves in a cylindrical waveguide with higher‐order derivative‐based boundary conditions and a sound absorbent lining. The mode‐matching method is employed to solve the governing boundary value problem, utilizing continuity conditions for pressure and velocity at waveguide interfaces. The objective is to establish a theoretical framework for analyzing and optimizing the acoustic performance of the waveguide, considering the influence of crucial parameters. The study's findings hold significant practical implications in acoustic engineering and noise control, enabling accurate prediction of acoustic wave behavior and facilitating the design of effective noise reduction measures and optimized sound‐absorbing materials in various applications. Additionally, the numerical techniques developed here can be extended to address more complex waveguide geometries and boundary conditions.

Study on the influence mechanism of polypropylene fiber on crack propagation of concrete with existing cracks under uniaxial compression

In the process of long-term service of concrete, cracks are inevitable, especially in the state of tension and compression, the crack expansion speed is accelerating, which seriously affects the service performance of concrete, and even causes major disasters. While polypropylene fiber has remarkable cracking resistance, there is a lack of theoretical analysis on crack initiation and path expansion of concrete cracks with existing cracks during the compression process. In order to analyze the inhibitory effect of fiber on the propagation of pre-existing cracks, we performed uniaxial compression tests on concrete prisms containing pre-existing cracks. Acoustic emission technology was used to monitor each test group and obtain relevant data on the cracking process of the specimens. GDEM software was used to simulate typical test conditions, and the results were compared with the test results to further explain the mechanism of crack propagation and fiber suppression. The results show that: (1) fiber can inhibit the initiation and propagation of tension wing cracks at the existing crack tip. The higher the fiber content, the shorter the symmetrical wing cracks become. (2) With the increase of fiber content (0 ∼ 4 kg/m3), the failure mode of polypropylene fiber-reinforced concrete prismatic specimens changes from tensile failure to tensile-shear failure, and finally shear failure. (3) The crack initiation stress and peak strength of prismatic specimens first increase and then decrease with the increase of fiber content. (4) The increase of fiber content delays the crack initiation time, prolongs the time to the disappearance of the peak of the acoustic emission signal, and prolongs the total time of the failure process.

Evaluating climate change impacts on reef environments via multibeam echosounder and Acoustic Doppler Current profiler technology

Crucial to the Earth's oceans, ocean currents dynamically react to various factors, including rotation, wind patterns, temperature fluctuations, alterations in salinity and the gravitational pull of the moon. Climate change impacts coastal ecosystems, emphasizing the need for understanding these currents. This study explores multibeam echosounder (MBES), specifically R2-Sonic 2020 instrument, offering detailed seabed information. Investigating coral reefs, rocky reefs and artificial reefs aimed to map seafloor currents movement and their climate change responses. MBES data viz. Bathymetry and backscatter were classified and acoustic doppler current profiler (ADCP) ground data were validated using random forest regression. Results indicated high precision in currents speed measurement i.e. coral reefs with 0.96, artificial reefs with 0.94 and rocky reefs with 0.97. Currents direction accuracy was notable in coral reefs with 0.85, slightly lower in rocky reefs with 0.72 and artificial reefs with 0.60. Random forest identified sediment and backscatter as key for speed prediction while direction relies on bathymetry, slope and aspect. The study emphasizes integrating sediment size, backscatter, bathymetry and ADCP data for seafloor current analysis. This multibeam data on sediments and currents support better marine spatial planning and determine biodiversity patterns planning in the reef area.

Developing a hybrid model with multiview learning for acoustic classification of Atlantic herring schools

AbstractAdvances in active acoustic technology have outpaced the ability to process and analyze the data in a timely manner. Currently, scientists rely on manual scrutiny or limited automation to translate acoustic backscatter to biologically meaningful metrics useful for fisheries and ecosystem management. The National Oceanic and Atmospheric Administration Northeast Fisheries Science Center has monitored the Atlantic herring population in the Gulf of Maine and Georges Bank since 1999 due to the stocks' important economic and ecological role for the commercial lobster industry. Manual scrutinization to identify Atlantic herring schools from the water column sonar data is time‐consuming and impractical for large‐scale studies. To automate this process, a hybrid model with multiview learning was proposed for automatic Atlantic herring school detection, which consists of two steps: (1) region‐of‐interest (ROI) detection and (2) ROI classification. The ROI detection step was designed to detect school‐like objects, and the ROI classification step was designed to distinguish Atlantic herring schools from other objects. The co‐training algorithm was employed for multiview learning as well as semi‐supervised learning. Within this framework, single‐view vs. multiview learning and supervised vs. semi‐supervised learning were evaluated and compared. Our results showed that multiview learning can improve the performance of the hybrid model in Atlantic herring school detection, and the utilization of unlabeled data is also helpful when the training set is small. The best‐performed model achieved an F1‐score of 0.804. This new framework provides an efficient and effective tool for automatic Atlantic herring school detection.

Target strength measurements of yellowfin tuna (Thunnus albacares) and acoustic discrimination of three tropical tuna species

Abstract Tropical tuna fisheries support some of the largest artisanal and industrial fisheries worldwide. Approximately 37% of the tropical tuna catch by industrial purse seiners is obtained from tuna associated with drifting fish aggregating devices (DFADs), where three tuna species coexist: skipjack (Katsuwonus pelamis), bigeye (Thunnus obesus), and yellowfin tuna (Thunnus albacares), with stocks subject to different health status. Purse seine fishers heavily rely on acoustic technology to detect and assess the quantity of tuna at DFADs. Yet, accurately distinguishing between species using solely acoustic methods is limited by insufficient knowledge about each species' acoustic response across frequencies. This study was carried out on six swimbladdered individuals belonging to two sets with mean lengths of 51.9 ± 9.5 and 52.9 ± 2 cm. It focuses on the frequency response obtained from ex situ measurements of yellowfin tuna recorded at 38, 70, 120, and 200 kHz, which revealed a flat response across frequencies, with b20 values of −72.4 ± 9, −73.2 ± 8, -72.3 ± 8, and −72.3 ± 9 dB, respectively. These results, contrast with previous findings on bigeye and skipjack, demonstrating the discrimination potential of acoustics in these three species. To harness this potential, a discrimination algorithm was developed.

Study on shear behavior and acoustic emission characteristics of precast concrete segmental cover beams with large key teeth

AbstractThe mechanical characteristics of segmental joints are pivotal in defining the comprehensive stress behavior of prefabricated assembled cover beams. In this research, direct shear tests were conducted on dry key‐tooth joints, and acoustic emission technology was employed for monitoring purposes. The shear failure mechanism was explored under a range of influential parameters. Building upon these observations, the study delved into the mechanical response of joints within segmental cover girders subjected to concurrent bending and shear forces. Specimen K‐3‐3 exhibited a higher shear carrying capacity compared to other specimens, indicating that the shear resistance of dry joints proportionally increases with the height of the specimen and the strength of the concrete. The carrying capacity of Specimen K‐4 was marginally lower than that of Specimens K‐3‐1 and K‐3‐2, suggesting that increasing the number of keys does not significantly impact the shear resistance of dry joints. Notably, Specimen K‐3 demonstrated exceptional shear carrying capacity, exhibiting minimal relative slip during failure, and streamlined the casting process. Consequently, these dry joints featuring large key teeth are deemed more appropriate for use as shear connectors in precast concrete segmental cover beams. Crack patterns in large key tooth precast concrete segmental cover beams propagate along the joints. A damage evolution model for the specimens, based on spatial b‐values and T‐values, visually depicts the damage extent in large key tooth precast concrete segmental cover beams. This model demonstrates excellent agreement with experimental results and provides a solid foundation for theoretical research and practical applications of large key tooth precast concrete segmental cover beams.

Research on particle separation microfluidic chip based on standing surface acoustic wave

Microparticle and cell separation is a key process in the study of cell properties, clinical diagnosis and disease treatment. In this paper, a particle separation method based on the combination of surface acoustic wave and microfluidic technology is proposed, which uses standing surface acoustic wave to achieve the separating of polystyrene microparticles of different sizes twice in a continuous flow. Through numerical simulation of the device model and particle trajectory simulation, the optimum particle separation parameters were determined. The particle separation microfluidic chip has successfully realized the particle separation. The separation yield of 5 μm particles is about 92.1%. The separation rate of 1 μm particles is about 83.3%.

Enhancing Preamplifier Design for Acoustic Emission Detection Instrument

With the development of the industry, the safety of pressure vessels is crucial for both production and personnel safety. The application of acoustic emission testing technology as a dynamic non-destructive testing method in the detection of pressure vessels is becoming increasingly prevalent. This paper presents the design of a low-frequency acoustic emission preamplifier with a frequency range of 30KHz to 200KHz and a gain of 20dB. The preamplifier is composed of amplification circuits, power supply circuits, and filtering components. By utilizing the PXR04 series high-sensitivity resonant acoustic emission sensor and Texas Instruments' OPA333 operational amplifier, along with a clever power supply design, effective signal amplification and system stability are ensured. Experimental results validate the correctness of the design, providing a feasible and effective solution for enhancing the performance of acoustic emission testing equipment.

Manufacturing of bioinspired Bouligand structures using ultrasound assisted 3D printing

Materials with bioinspired Bouligand structures provide a new approach to explore isotropic fiber-reinforced composites. However, it is challenging to manufacture composites with various fibers along with a three-dimensional helical structure. In this work, to accomplish the alignment of a three-dimensional (3D) helical structure of fibers in a composite material, an acoustically aligned fiber technology was incorporated with a rotating mechanism in a stereolithography 3D printer. Firstly, the formation process of acoustic standing wave was simulated and the relationship between standing wave parameters and planar line arrays was then established. Secondly, Bouligand composites with various parameters were fabricated using an acoustic-assisted 3D printing technology and the effect of the angle between the interlayer fiber arrays on the mechanical properties was experimentally measured. Finally, heat sink and meniscus structures with Bouligand structure were fabricated using carbon nanofiber and glass nanofiber, respectively. The 3D printing processing method integrating acoustic alignment technology and rotating mechanism provides a new method for fabrication of composite materials with complex fiber structures.

A review of the Research on Tunnel Lining Voiding Detection Based on Acoustic Vibration Method

In the study of nondestructive testing technology for tunnel lining voiding detection, the traditional nondestructive testing technology has many drawbacks such as poor detection accuracy, high subjectivity, and easy to be interfered with, etc., and the combination of acoustic vibration method and deep learning technology has the problems of uneven distribution of the data set, poor interpretability, and other problems that are difficult to be applied to industrial applications, which summarizes the current acoustic vibration testing technology and its application to the study of tunnel lining voiding. Firstly, the non-destructive testing techniques used in the current tunnel lining voiding detection research are sorted out, and then a variety of tunnel lining voiding detection research methods based on acoustic vibration method with potential applications in the industrial field are analyzed, followed by an overview of the current situation from the point of view of deep learning combined with the acoustic vibration method for the detection of tunnel lining voiding, and then the direction of the next step of the research is discussed and analyzed. The full paper is summarized, and future challenges are pointed out.

Damage Monitoring of Regularly Arrayed Short-Fiber-Reinforced Composite Laminates under Tensile Load Based on Acoustic Emission Technology.

Carbon-fiber-reinforced polymer (CFRP) composites are widely used in lightweight structures because of their high specific strength, specific modulus, and low coefficient of thermal expansion. Additionally, the unidirectionally arrayed chopped strand (UACS) laminates have excellent mechanical properties and flowability, making them suitable for fabricating structures with complex geometry. In this paper, the damage process of UACS quasi-isotropic laminates under tensile load was tested using acoustic emission detection technology. The mechanical properties and damage failure mechanism of UACS laminates were studied combined with finite element calculation. By comparing and analyzing the characteristic parameters of acoustic emission signals such as amplitude, relative energy, and impact event, it is found that acoustic emission behavior can accurately describe the damage evolution of specimens during loading. The results show that the high-amplitude signals representing fiber fracture in continuous fiber laminates are concentrated in the last 41%, while in UACS laminates they are concentrated in the last 30%. In UACS laminates, more of the damage is caused by matrix cracks and delamination with medium- and low-amplitude signals, which indicates that UACS laminates have a good suppression effect on damage propagation. The stress-strain curves obtained from finite element analysis agree well with the experiment results, showing the same damage sequence, which confirms that the model described in this research is reliable.

Failure behaviors and acoustic emission characteristics of flawed granite of different grain sizes: Insights from true triaxial experiments with a free face

In this study, a group of experiments using true triaxial stress conditions with free face loading are performed on granite specimens with non-penetrating double flaws. The crack development and failure characteristics of these specimens are explored by integrating video of the free face and acoustic emission technology, with the combination of the four different intermediate principal stresses and three different grain sizes of the granite chosen as variables. First, surface flaws with a depth of 50 mm are found to have limited influence on the specimen’s failure mode. The intermediate principal stress has a greater effect as it inhibits the development of surface cracks; however, surface cracks develop much more readily in coarse-grained specimens than in other specimens. Second, when the intermediate principal stress exceeds 10 MPa, the rock burst failure phenomenon occurs in the specimen. Third, irrespective of changes in the intermediate principal stress and granite specimen grain size, the specimens primarily fail by tensile-shear failure and shear failure. Extending inward from the free face in the σ3 direction, according to the failure types, the failure types can be classified into tensile failure, shear failure, and tensile-shear failure. Finally, using the stress state synthesis method, the specimen’s stress state and crack distribution mechanism on the σ2 loading plane are analyzed.

Topology Optimization Design Method for Acoustic Imaging Array of Power Equipment.

Acoustic imaging technology has the advantages of non-contact and intuitive positioning. It is suitable for the rapid positioning of defects such as the mechanical loosening, discharge, and DC bias of power equipment. However, the existing research lacks the optimization design of microphone array topology. The acoustic frequency domain characteristics of typical power equipment are elaborately sorted out. After that, the cut-off frequencies of acoustic imaging instruments are determined, to meet the needs of the full bandwidth test requirements. Through a simulation calculation, the circular array is demonstrated to be the optimal shape. And the design parameters affect the imaging performance of the array to varying degrees, indicating that it is difficult to obtain the optimal array topology by an exhaustive method. Aimed at the complex working conditions of power equipment, a topology optimization design method of an acoustic imaging array for power equipment is proposed, and the global optimal solution of microphone array topology is obtained. Compared with the original array, the imaging performance of the improved LF and HF array is promoted by 54% and 49%, respectively. Combined with the simulation analysis and laboratory test, it is verified that the improved array can not only accurately locate the single sound source but also accurately identify the main sound source from the interference of the contiguous sound source.