Search Results (129)

Internal leakage within the valve body constitutes a severe potential safety hazard in industrial fluid control systems, attributable to its high concealment and the resultant difficulty in detection via conventional methodologies. Acoustic emission (AE) technology, functioning as an efficient non-destructive testing approach, is capable of capturing the transient stress waves induced by leakage, thereby furnishing an effective means for the real-time monitoring and quantitative assessment of internal leakage within the valve body. This paper conducts a systematic review of the theoretical foundations, signal-processing methodologies, and the latest research advancements related to the technology for detecting internal leakage in the valve body based on acoustic emission. Firstly, grounded in Lechlier’s acoustic analogy theory, the generation mechanism of acoustic emission signals arising from valve body leakage is elucidated. Secondly, a detailed analysis is conducted on diverse signal processing techniques and their corresponding optimization strategies, encompassing parameter analysis, time–frequency analysis, nonlinear dynamics methods, and intelligent algorithms. Moreover, this paper recapitulates the current challenges encountered by this technology and delineates future research orientations, such as the fusion of multi-modal sensors, the deployment of lightweight deep learning models, and integration with the Internet of Things. This study provides a systematic reference for the engineering application and theoretical development of the acoustic emission-based technology for detecting internal leakage in valves. Full article

Aiming to mitigate engineering risks such as tunnel face collapse and equipment jamming caused by poor geological conditions during the construction of tunnel boring machines (TBMs), this study proposes a TBM surrounding rock grade prediction method based on multi-source feature fusion. Firstly, a multi-source dataset is established by systematically integrating TBM tunnelling parameters, horizontal acoustic profile (HSP) detection data and three-dimensional geological spatial information. In the data preprocessing stage, the TBM data is cleaned and divided according to the mileage section, the statistical characteristics of key tunnelling parameters (thrust, torque, penetration, etc.) are extracted, and the rock fragmentation index (TPI, FPI, WR) is fused to construct a composite feature vector. The Direct-LiNGAM causal discovery algorithm is innovatively introduced to analyse the nonlinear correlation mechanism between multi-source features, and then a hybrid model, TRNet, which combines the local feature extraction ability of convolutional neural networks and the nonlinear approximation advantages of Kolmogorov–Arnold networks, is constructed. Verified by a real tunnel project in western Sichuan, China, the prediction accuracy of TRNet for surrounding rock grade on the test set reaches an average of 92.15%, which is higher than other data-driven methods. The results show that the prediction method proposed in this paper can effectively predict the surrounding rock grade of the tunnel face during TBM tunnelling, and provide decision support for the dynamic regulation of tunnelling parameters. Full article

Progressive damage evolution in rock masses serves as the fundamental mechanism driving geological hazards by controlling deformation patterns and failure predictability. To address the critical challenge of predicting fracture behaviors in heterogeneous geological media, this study pioneers the integration of real-time computed tomography (CT) scanning and acoustic emission (AE) monitoring to investigate self-organized criticality and fracture predictability in Cretaceous sandstone under uniaxial compression. By systematically analyzing internal structural evolution and damage parameters, this established a multiparameter framework to characterize self-organized processes and critical phase transitions during progressive fracturing. Key findings include the following: (1) Distinct critical thresholds emerge during yield-stage self-organization, marked by abrupt transitions in AE signals and crack metrics—from microdamage coalescence initiating volumetric expansion (first critical point) to macrocrack nucleation preceding peak strength (second critical point). (2) AE-crack evolution follows power–law statistics, where elevated scaling exponents (r > 0.85) correlate with intensified nonlinear damage, accelerated localization, and progressive rate enhancement. Yield-stage power–law acceleration provides quantifiable failure precursors. (3) Yield-stage damage patterns exhibit 85% similarity with terminal failure configurations, confirming yield-stage as the definitive precursor with critical temporal signatures for failure prediction. A conceptual framework integrating multiparameter responses (AE signals, crack metrics) was developed to decipher self-organized critical phase transitions during deformation-failure processes. This work establishes methodological foundations for investigating damage mechanisms and predictive strategies in heterogeneous rock systems. Full article

Acoustic metamaterials have been widely applied in fields such as sound insulation and noise reduction due to their controllable band structures and unique abilities to manipulate low-frequency sound waves. However, there exists a highly nonlinear mapping relationship between their structural parameters and performance responses, which causes traditional design methods to face the problems of inefficiency and poor generalization. Therefore, this paper proposes a bidirectional modeling framework based on deep learning. We constructed a forward prediction network that integrates an attention mechanism, a multi-scale feature fusion, and a reverse design model that combines an improved autoencoder and cascaded neural network to efficiently model the dispersion performance of acoustic metamaterials. In the feedforward network, the improved forward prediction model shows superior performance compared to the traditional Convolutional Neural Network model and the model based only on the Convolutional Block Attention Module attention mechanism, with a prediction accuracy of 99.65%. It has better fitting ability and stability in the high-frequency part of the dispersion curve. In the inverse network part, compression of the high-dimensional dispersion curves by an improved autoencoder reduces the training time by about 13.5% without significant degradation of the inverse prediction accuracy. The proposed network model provides a more efficient method for the design of metamaterials. Full article

One of the quintessential goals of musical instrument acoustics is to improve the perceived sound produced by, e.g., a violin. To achieve this, the connections between physical (mechanical and geometrical) properties and perceived sound output need to be understood. In this article, a single facet of this complex problem will be discussed using experimental results obtained for six violins of varying back arch height. This is the first investigation of its kind to focus on back arch height. It may serve to inform instrument makers and researchers alike about the variation in sound that can be achieved by varying this parameter. The test instruments were constructed using state-of-the-art methodology to best represent the theoretical case of changing back arch height on a single instrument. Three values of back arch height ($12.1$, $14.8$ and $17.5$ mm) were investigated. The subsequent perceptual tests consisted of a free sorting task in the playing situation and three two-alternative forced choice listening tests. The descriptors “round” and “warm” were found to be linked to back arch height. The trend was non-linear, meaning that both low- and high-arch height instruments were rated as possessing more of these descriptors than their medium-arch height counterparts. Additional results were obtained using stimuli created by hybrid synthesis. However, these could not be linked to those using real playing or recordings. The results of this study serve to inform violin makers about the relative importance of back arch height and its specific influence on sound output. The discussion of the applied methodology and interpretation of results may serve to inform researchers about important new directions in the field of musical instrument acoustics. Full article

Background: This study examined the relationship between hearing device price and sound quality. Method: A novel consumer-centric metric of sound quality (“SoundScore”) was used to assess hearing devices’ audio performance. Each hearing device is tested with two fittings. The “Initial Fit” is designed to approximate the most likely fitting for an individual with a mild-to-moderate sloping sensorineural hearing loss. The “Tuned Fit” includes adjusting parameters optimized to hit prescriptive fitting targets (NAL NL2) on an acoustic manikin. Each fitting is evaluated across five dimensions. Both fittings are combined using a weighted average to create a single number from 0 to 5 representative of a device’s overall audio performance. Seventy-one hearing devices were tested. Results: A strong positive correlation was found between hearing device price and SoundScore. The average SoundScore increased dramatically as the price approached USD 1000, with marginal improvements beyond this point. SoundScore was consistently poor for devices under USD 500, highly variable between USD 500–1000, and consistently good over USD 1000. Conclusions: There is a strong but nonlinear relationship between hearing device price and sound quality. This information can aid consumers in making informed decisions while also assisting hearing healthcare professionals in providing comprehensive guidance to their patients. Full article

This paper is about the characteristics of and a method to recognize the onset of limit cycle thermoacoustic oscillations in a gas turbine-like combustor with a premixed turbulent methane/air flame. Information on the measured time series data of the pressure and the OH* chemiluminescence is acquired and postprocessed. This is performed for a combustor with variation in two parameters: fuel/air equivalence ratio and combustor length. It is of prime importance to acknowledge the nonlinear dynamic nature of these instabilities. A method is studied to interpret thermoacoustic instability phenomena and assess quantitatively the transition of the combustor from a stable to an unstable regime. In this method, three-phase portraits are created on the basis of data retrieved from the measured acoustics and flame intensity in the laboratory-scale test combustor. In the path to limit cycle oscillation, the random distribution in the three-phase portrait contracts to an attractor. The phase portraits obtained when changing operating conditions, moving from the stable to the unstable regime and back, are analyzed. Subsequently, the attractor dimension is determined for quantitative analysis. On the basis of the trajectories from the stable to unstable and back in one run, a study is performed of the hysteresis dynamics in bifurcation diagrams. Finally, the onset of the instability is demonstrated to be recognized by the 0-1 criterion for chaos. The method was developed and demonstrated on a low-power atmospheric methane combustor with the aim to apply it subsequently on a high-power pressurized diesel combustor. Full article

Fluororubber sealing products are widely used in nuclear power equipment, and the degree of degradation of their mechanical properties directly affects the sealing performance, which in turn affects the overall safety of nuclear power units. In order to quantitatively evaluate the degradation of the mechanical properties of fluororubber, the theory of ultrasonic propagation in fluororubber was studied. A second-order generalized Maxwell viscoelastic model was constructed in a small strain scenario of high-frequency harmonic vibration to describe the correlation between the mechanical properties and acoustic parameters. A nondestructive evaluation method for mechanical performance degradation using ultrasonic waves based on the nonlinear fitting of the model parameters was proposed. A control experiment was designed using O-rings that had been in service and those that had not yet been used in nuclear power, and mechanical tensile tests and electron microscopy microscopic analyses were conducted. The results showed that the overall elastic modulus of the used sealing ring (2.97 ± 0.15 GPa) was significantly higher than that of the unused sealing ring (2.75 ± 0.22 GPa), consistent with the results of the mechanical tensile tests. However, the sound attenuation coefficient of the unused sealing ring was significantly higher than that of the used sealing ring. Therefore, the ultrasonic evaluation of the mechanical performance degradation of fluororubber based on the viscoelastic model is a nondestructive testing method with engineering application potential. Full article

Underwater acoustic signals typically exhibit non-Gaussian, non-stationary, and nonlinear characteristics. When processing real-world underwater acoustic signals, traditional multivariate entropy algorithms often struggle to simultaneously ensure stability and extract cross-channel information. To address these issues, the improved multivariate multiscale sample entropy (IMMSE) algorithm is proposed, which extracts the complexity of multi-channel data, enabling a more comprehensive and stable representation of the dynamic characteristics of complex nonlinear systems. This paper explores the optimal parameter selection range for the IMMSE algorithm and compares its sensitivity to noise and computational efficiency with traditional multivariate entropy algorithms. The results demonstrate that IMMSE outperforms its counterparts in terms of both stability and computational efficiency. Analysis of various types of ship-radiated noise further demonstrates IMMSE’s superior stability in handling complex underwater acoustic signals. Moreover, IMMSE’s ability to extract features enables more accurate discrimination between different signal types. Finally, the paper presents data processing results in mechanical fault diagnosis, underscoring the broad applicability of IMMSE. Full article

Acoustic nonlinearity derived from microstructural evolution of metallic materials during plastic deformation has been found to be a promising nondestructive technique to identify early stage plastic damage in metallic structural components. In the current investigation, the propagation of longitudinal ultrasonic waves in plastically deformed 35CrMoA steel plates was simulated using finite element (FE) methods based on the theory of dislocation-induced acoustic nonlinearity to establish the relationship between acoustic nonlinearity parameters and plastic strain. Experiments were conducted to validate the numerical model. Both simulated and experimental results demonstrate a monotonic increase in the acoustic nonlinearity parameter with applied plastic strain. The simulated ultrasonic nonlinear parameters deviate from experimental measurements in a two-stage pattern. In the low-strain regime (plastic strain < 8.5%), FE predictions underestimate experimental values, possibly due to dislocation entanglement in high-density regions that restricts dislocation mobility and suppresses acoustic nonlinearity. The FE model overestimates the parameters when plastic strain exceeds about 8.5%. This reversal is related to the formation of dislocation cells and walls with enhanced acoustic nonlinearity. Full article

This study addresses the challenge of predicting acoustic source strength in freshwater environments, focusing on frequencies between 100–400 kHz. Acoustic signal attenuation is inherently frequency-dependent and influenced by water properties as well as the total propagation path of the acoustic wave, complicating the accurate determination of source strength. To address this challenge, we developed a non-linear regression model for solving the inverse problem of attenuation correction in reflected signals from typical aquatic reflectors, addressing the current absence of robust correction tools in this frequency range. The novelty of our approach lies in designing a non-linear regression framework that incorporates key physical parameters—signal energy, propagation distance, and frequency—enabling accurate source strength prediction. Using an experimental setup comprising ultrasonic transducers and a signal generator under controlled conditions, we collected a comprehensive dataset of 366 samples. The results demonstrate that our proposed model achieves reliable source strength prediction by simplifying Thorpe’s equation for freshwater environments. This research represents a significant advancement in underwater acoustics, providing a practical and reliable tool for source strength estimation in freshwater systems. The developed methodology may have broad applications across sonar technology, environmental monitoring, and aquatic research domains. Full article

Modeling and system identification are critical for the design, simulation, and navigation of underwater vehicles. This study presents a six degree-of-freedom (DoF) nonlinear model for a finless underactuated underwater vehicle, incorporating port-starboard symmetry and cross-flow terms. Then, hydrodynamic damping parameters are identified using an optimized Extended Kalman Filter (EKF), establishing a steady validation framework for computational fluid dynamics (CFD) simulation coefficients. Additionally, system identification is further enhanced with a Long Short-Term Memory (LSTM) neural network and a comprehensive dataset construction method, enabling time-series predictions of linear and angular velocities. To mitigate position divergence in dead reckoning (DR) caused by LSTM, a Nonlinear Explicit Complementary Filter (NECF) is integrated for attitude estimation, providing accurate yaw computation and reliable localization without dependence on acoustic sensors or machine vision. Finally, validation and evaluation are conducted to demonstrate model accuracy, EKF convergence, and the reliability of LSTM-based navigation. Full article

In this study, the effects of pressure anisotropy and viscosity on the propagation of shock waves in spin-polarized degenerate quantum magnetoplasma are studied under the influence of the streaming energy of ion beams. The effects of different suitable plasma parameters on the shock wave’s potential profile are studied using the steady state solution of the Zakharov–Kuznetsov–Burgers (Z–K–B) equation, as well as the numerical simulation of the governing non-linear Z–K–B equation. First-order analysis of the non-linear wave propagation depicted a new beam-induced stable mode whose Mach number may be subsonic or supersonic depending on the anisotropic pressure combination in the presence of different spin density polarization ratios. This is the first observation of this new beam-induced stable mode in ion beam plasma, apart from the other existing modes of ion beam plasma systems, namely, the fast beam mode, the slow beam mode, the inherent ion acoustic mode, and the coupled mode, which also has unique propagation characteristics compared to the other modes. The spin density polarization ratio of spin-up and spin-down electrons have an unprecedented effect on the polarity and the direction of propagation of different shock wave modes in such plasma systems. Apart from the spin effect, anisotropic pressure combinations, as well as the viscosity of ions and ion beams, also play an outstanding role in controlling the nature of propagation of shock waves, especially in the newly detected beam-induced stable mode, and depending on the viscosity parameters of ions and ion beams, both oscillatory and monotonic shock waves can propagate in such plasma. Full article

Lab-on-a-Chip devices based on tilted-angle standing surface acoustic waves (tasSAWs) emerged as a promising technology for multidimensional particle separation, highly selective in particle size and acoustic contrast factor. For this active separation method, a tailored acoustic field is used to focus and separate particles on stationary pressure nodes by means of the acoustic radiation force. However, additional non-linear acoustofluidic phenomena, such as the acoustically induced fluid flow or dielectrophoretic effects, are superimposed on the separation process. To obtain a particle separation of high quality, control parameters that can be adjusted during the separation process as well as design parameters are available. The latter are specified prior to the separation and span a high-dimensional parameter space, ranging from the acoustic wavelength to the dimensions and materials used for the microchannel. In this paper, the physical mechanisms to control and design tasSAW-based separation devices are reviewed. By combining experimental, semi-analytical, and numerical findings, a critical channel height and width are derived to suppress the influence of the acoustically induced fluid flow. Dealing with the three-dimensional nature of the separation process, particles are focused at different height levels of equal force balance by implementing a channel cover of high acoustic impedance while achieving an approx. three-times higher acoustic pressure. Using this improved channel design, the particle shape is identified as an additional separation criterion, rendering the continuous acoustofluidic particle separation as a multidimensional technology capable of selectively separating microparticles below 10 μm with regard to size, acoustic contrast, and shape. Full article

An exact numerical and approximate analytical description of solitary acoustic pulses with a large difference in spatial gradients of parameters in different directions has been obtained in viscous liquids using this small parameter. The method of special initial-boundary conditions obtained during analyzing the hydrodynamic equations has been applied to describe the peculiarities of this nonlinear phenomenon. Waves of this type exist in the presence of two- or three-dimensional inhomogeneity of the initial disturbances and retain a spatial structure along the direction of propagation when traveling long distances. At the same time, it is possible to regulate the pressure drop and the speed of the acoustic signal, which creates unique conditions for a special force effect or information transmission. The efficiency of their use in such processes as metal dissolution, solvent extraction and mass transfer under the conditions of resonance exposure of ultrasound was evaluated. Fine details of exciting the nonlinear impulse with the necessary properties have been analyzed to demonstrate a possible way to a new technology of successfully treating any different specimens, materials and constructions for a long distance between the source of radiation and the position of the treatment. The use of such pulses opens up new opportunities for remote acoustic force impact on various objects, as well as for the transmission of information. Full article