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As a core fundamental component in various large-scale mechanical systems, bearings play a critical role in ensuring the safe and reliable operation of equipment, making high-precision detection and imaging of internal defects of significant theoretical and engineering importance. To address the challenges associated with bearings featuring complex curved surfaces, this study proposes a high signal-to-noise ratio ultrasonic imaging method based on the delay multiply and sum (DMAS) algorithm. In the experiments, a wedge in combination with an ultrasonic phased-array transducer was employed to inspect internal flat-bottom hole defects in bearings using oblique ultrasonic incidence. Signal-to-noise ratio (SNR), array performance index (API), and other evaluation metrics were introduced to quantitatively assess the imaging performance for different types of damage. The experimental results demonstrate that the surface-corrected p-DMAS imaging algorithm exhibits superior performance across all image quality metrics, achieving a maximum SNR improvement of 25.8 dB and an API increase of up to 8.4, thereby significantly enhancing defect detection capability. This method provides a novel approach and practical solution for in situ nondestructive testing of bearing-like curved structures.
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In recent years, advances in semiconductor silicon wafer manufacturing have increased the demand for accurate detection of subsurface defects. When inspecting microcracks far smaller than the wavelength, nonlinear Lamb waves offer distinct advantages such as high efficiency, high sensitivity, and nondestructive evaluation. However, their application in silicon wafer inspection remains limited, partly due to the unclear relationship between nonlinear Lamb wave signal characteristics and subsurface microcrack features. In this work, finite element models of Lamb wave propagation in silicon wafers with subsurface microcracks are established. The Lamb wave mode pair S0-s0, satisfying phase-velocity matching, is employed to investigate how the acoustic nonlinearity parameter (ANP) of the second-harmonic correlates with propagation distance and microcrack characteristics. Simulation results indicate that the ANP increases with propagation distance, and the presence of subsurface microcracks significantly amplifies its amplitude. Moreover, the relative ANP increases with the number,length, density of subsurface microcracks, and subsurface damage layer thickness. Additionally, for a given density, the length of subsurface microcracks has a more significant influence on the relative ANP than their number. This study illustrates the potential of nonlinear Lamb waves for detecting subsurface microcracks in silicon wafers and provides simulation-based validation for its feasibility.
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To address the challenge of non-destructively characterizing deep three-dimensional residual stress fields in critical load-bearing hot-section components of domestically developed large wide-body aircraft engines, this study investigates ultrasonic-based methods for non-destructive residual stress characterization and imaging. An ultrasonic acoustoelastic theoretical model capable of describing the influence of arbitrary three-dimensional stresses is established, revealing a quantitative relationship between the relative velocity variations of ultrasonic bulk longitudinal waves and triaxial stresses. By developing an ultrasonic wave-propagation simulation framework for components containing residual stresses, multi-angle ultrasonic transmission data are designed and acquired for representative high-temperature alloy forgings. Two imaging approaches are proposed: a tomographic imaging method based on iterative reconstruction algorithms and an inversion imaging method based on neural networks. The results demonstrate that the tomographic approach can sensitively capture the characteristic “tensile core-compressive surface” stress distribution within the forging and exhibits high sensitivity to process-induced asymmetric distributions. The neural network method, in contrast, shows strong nonlinear fitting capability for complex patterns and yields smaller average errors in high-stress regions. The two methods are complementary, their inversion results remain at the same stress level as the ground truth and effectively reflect the magnitudes and distributions of radial, circumferential, and axial residual stresses within the actual forging. The proposed methodology provides important data support for ensuring the dimensional stability, reliability, and in-service safety of critical load-bearing hot-section components in aero-engines.
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The identification of crack tips in total focusing method (TFM) is easily affected by diffraction waves. In this study, the ultrasonic TFM based on Otsu thresholding is proposed for crack characterization. The full-matrix amplitude map is first constructed from the full matrix capture (FMC) data. Then, the adaptive algorithm of Otsu threshold is applied to automatically segment the reflection and diffraction regions. Only the reflection signals are used for delay-and-sum process and imaging to avoid diffraction interference and improve efficiency. Detection results of internal cracks in aluminum alloy show that the proposed method outperforms the conventional TFM using complete FMC data in crack measurement and imaging efficiency. The error of crack length is less than 0.3 mm, the error of angular is within 2.0°, and the required imaging time is reduced by more than 60%.
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To address the challenge of extracting subtle ultrasonic defect features in low signal-to-noise ratio environments, this study proposes a gated residual and dual-attention collaborative enhancement network for low SNR ultrasonic signals. Based on convolutional neural network, the model adopts a ‘residual block squeeze-excitation(SE) module-pooling’ cascaded structure: a standard SE module is embedded in the residual block for initial channel screening, a locally enhanced SE module is used at the end of network stages to focus on peak signals, and gated residual connections are employed to dynamically preserve original subtle features, thus realizing collaborative optimization of noise suppression and feature enhancement. Experimental results show that the improved model achieves a mean root mean square error (RMSE) of 0.068 3 and a mean absolute error (MAE) of 0.047 1, which are 49.7% and 41.7% lower than those of the baseline CNN, respectively. It also outperforms models with only a single attention mechanism or residual blocks, verifying the superiority of dual-mechanism collaboration, while exhibiting excellent training stability and maintaining high accuracy in low SNR environments. In conclusion, the proposed model effectively overcomes the bottlenecks of noise interference and subtle feature learning. Its prediction accuracy, anti-interference capability, and stability are significantly superior to traditional methods and existing models, providing an efficient technical solution for ultrasonic non-destructive testing of steel pipes with important industrial application value.
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Based on the GPU-parallelized algorithm of the time-domain spectral element method (SEM), this study investigates the S0 mode guided waves in anisotropic plates. Parallelization is achieved by integrating high-order spectral element discretization with the CUDA computing platform, thereby establishing a numerical model for guided wave propagation in composite plates. The proposed model accurately simulates the excitation and propagation processes of guided waves in composite plates, extracts the characteristics of the S0 mode, calculates its wave velocity, and subsequently plots the distribution curves of S0 mode wave velocity. To validate the model, an experimental system was set up using piezoelectric sensors as excitation units to conduct S0 mode guided wave propagation tests on T300 composite plates. By incorporating element-level parallel computation and a matrix-free assembly strategy, the proposed method significantly improves computational efficiency and remarkably reduces memory consumption. Numerical verification demonstrates that the method achieves high accuracy while offering superior computational performance and resource efficiency compared with traditional SEM. The simulation results show excellent agreement with the experimental measurements and accurately capture the wave-velocity curve of the S0 mode, thereby verifying the accuracy and feasibility of the proposed parallel time-domain spectral element method. This study offers an effective technical route for the simulation of guided wave propagation in composite plates and demonstrates broad prospects for application in the field of health monitoring of composite plates.
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To address the challenge of extracting weak nonlinear effects, a method for extracting mixed nonlinear components is proposed based on sliding correlation analysis. Finite element simulations are conducted to investigate the influence of time window width on the extraction results of mixed components. A sine signal modulated with a Hann window is selected as the reference signal, and when the time window width matches the excitation signal length, the extraction of mixed nonlinear components achieves the best results. Mixed nonlinear detection experiments are carried out on specimens with different bonding strengths, and the mixed components are extracted using three different methods. The results indicate that, compared with the three-excitation difference and polarity reversal methods, the sliding correlation analysis method simplifies the nonlinear detection process, allowing accurate extraction of the nonlinear mixed-frequency components using only a single detection signal. The normalized nonlinear coefficient obtained can effectively characterize the bond strength of the adhesive structure.
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The propagation behavior of Lamb waves in variable thickness plates is complex and exhibits significant dispersion effects, which leads to the difficulty of defect localization and imaging. A defect imaging method for slowly varying-thickness plates based on a Lamb wave propagation model is proposed in this paper. A Lamb wave propagation model for variable thickness plates is established, enabling the prediction of response signals through segmented constant thickness approximation and dispersion curve interpolation. A backward propagation phase compensation algorithm is introduced to eliminate signal distortion induced by dispersion effects. Combined with a delay-and-sum imaging algorithm, this approach achieves high-resolution defect imaging in the slowly varying-thickness plates. Numerical simulations and experimental studies are conducted to validate the proposed method. Numerical results demonstrate a positioning error of approximately 5.8 mm for an 8 mm diameter circular hole defect in a 500 mm×500 mm aluminum plate with thickness varying linearly from 2 mm to 4 mm. Experimental results confirm clear defect visualization with a positioning error of about 10 mm, verifying the method’s applicability in defect detection for slowly varying-thickness plates.
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A novel vortex ultrasonic hole-detection methodology is proposed to address the pressing need for rapid and cost-effective internal defect detection within materials, leveraging the unique properties of vortex ultrasound.A systematic analysis was conducted on the propagation characteristics of vortex ultrasound within titanium alloy materials. The research findings reveal that the second harmonic signal detected at the center of the vortex ultrasound field can effectively ascertain the presence of internal pores in the material. Furthermore, the signal amplitude diminishes as the radial distance and depth between the pore and the center position increase, thereby defining the effective radial and depth detection ranges of vortex ultrasonic inspection and enabling qualitative localization of the pore’s position. Concurrently, the amplitude at the vortex ultrasound center position escalates with the enlargement of the pore size, indicating its potential for quantitative assessment of pore dimensions. Numerical simulation results further corroborate that variations in the presence, position, and size of pores induce alterations in the amplitude at the vortex ultrasound center, thereby validating the efficacy and feasibility of vortex ultrasound for detecting pore defects in titanium alloys. This study is anticipated to furnish novel theoretical insights and methodologies for the swift detection of internal pores in materials.
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To improve the “pitch-catch” detection mode in the method for micro-damage detection based on the static component of nonlinear ultrasound, a detection method based on the pulse-echo approach is proposed, which requires only a straight probe to achieve both transmission and reception of ultrasonic waves.Taking an aluminum plate specimen as an example, finite element simulations and experimental measurements were conducted.Nonlinear ultrasonic longitudinal waves were excited using a single straight probe, and their reflected signals were collected.The fundamental frequency and static component were extracted from these signals, and the relative nonlinear coefficient was calculated to evaluate the degree of plastic damage in the aluminum plate.The results show that when using an ultrasonic transducer with a center frequency of 5 MHz for excitation and reception, the static component of the reflected wave can be effectively obtained, verifying the feasibility of the single transducer pulse-echo method for acquiring the static component.The relative nonlinear coefficient of the static component of the reflected wave increases with the thickness of the aluminum plate and the degree of plastic damage, further demonstrating the effectiveness and applicability of this method for micro-damage detection.
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To investigate the effect of machining parameters on the surface quality of high volume fraction silicon carbide particle reinforced aluminum matrix composites (SiCp/Al), SiCp/Al composites with 45% and 60% volume fractions were selected and subjected to rotary ultrasonic grinding under an ultrasonic amplitude range of 0~8 μm, spindle speed of 6 000~21 000 r/min, and feed rate of 20~220 mm/min. The surface morphology and roughness (Ra) were analyzed using scanning electron microscop and a surface roughness meter, and the formation mechanism was studied by examining the influence of ultrasonic vibration on tool trajectory and cutting force. The results show that when the ultrasonic amplitude is controlled within 4 μm, the surface quality of SiCp/Al is significantly improved, with surface Ra reduced by 32.1% (45% volume fraction) and 21.4% (60% volume fraction). Additionally, a high spindle speed, low feed rate, and small depth of cut further reduce surface Ra. The material volume fraction has a notable impact on the machined surface quality: the surface Ra of the 60% volume fraction material is higher than that of the 45% volume fraction material, indicating that materials with higher volume fractions are more prone to surface quality defects. Rotary ultrasonic grinding produces high frequency impact and intermittent cutting effects, which reduce cutting force and improve surface quality.
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In order to effectively achieve low-frequency broadband sound absorption and obtain high hydrostatic pressure resistance within low thickness limits, a multi-cell parallel coupling anechoic coating structure with a thickness of less than 40 mm is proposed. The structure has several acoustic cells with different structures, and each acoustic cell consists of rubber and metal. The optimal size parameters of the multi-cell anechoic coating structure were determined by combining the finite element method and genetic algorithm optimization. It achieves a broadband sound absorption effect in which the sound absorption coefficient is evenly distributed from 510 Hz to 10 kHz frequency band, and the average sound absorption coefficient exceeds 0.96. From the perspective of displacement field, energy dissipation power distribution, and equivalent acoustic impedance matching, the mechanism and characteristics of broadband sound absorption caused by cooperative coupling are explained respectively. The results show that different structures and sizes between unit cells will affect the structural vibration and wave mode conversion efficiency within the unit cell. The sound absorption strength of each unit cell at different frequency bands is used to complement each other, and combined with optimization methods, the sound absorption can be effectively broadened bandwidth.
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Improving the stability of all-inorganic cesium bromide-lead perovskite quantum dots (CsPbBr3 PeQDs) is of great importance in terms of enhancing the device performance and expanding their application areas.A series of Zn2+ doped CsPbBr3 PeQDs samples were prepared by ligand-assisted reprecipitation method at room temperature, and the spectral tuning of 520~513 nm was realized.Their photoluminescence (PL) intensity could be enhanced by 63% compared to the undoped CsPbBr3 samples. Subsequently, CsPbBr3:Zn/AGs composite samples were prepared by in situ growth of PeQDs on superhydrophobic silica aerogels(aerogels,AGs). CsPbBr3 PeQDs were effectively protected from exposure to unfavorable factors such as light and oxygen in the environment by the protective matrix formed by AGs, and the PL intensity of the composite samples was decreased by 17% at room temperature for 20 days, and only 14% under the continuous action of ultraviolet light for 120 min. The synergistic effect of Zn2+ doping and AGs encapsulation significantly enhances the optical properties and environmental stability of CsPbBr3 quantum dots, enabling them to better meet the requirements of practical applications and promoting their development in the field of optoelectronics.