Ultrasonics最新文献

The transmission of compressional ultrasonic waves into a rigid and dense solid with a doubly-curved surface is impeded when the solid is placed in a liquid medium and its surface is irradiated with waves traveling through the liquid. Measurable power transmission is only possible when the incident ultrasonic beam is close to normal to the surface. This condition is difficult to realize when the waves are excited and detected by a linear array of transducers and limits the possibility of forming cross-sectional images of the solid from the array data. Here, it is shown that the interior of the solid can be imaged with enhanced fidelity if the water is frozen. The high speed of compressional waves in polycrystalline ice (approximately 4000 ms^-1) along with its rigid behavior ensure that ultrasonic waves can be transmitted through the surface over a broad range of angles of incidence. However, due to the double curvature, the rays that form the ultrasonic beam can be deflected outside the array azimuthal plane after entering the solid. Therefore, the two-dimensional images obtained from the linear array data may not be consistent with the fully three-dimensional structure of the ray paths. The analysis of this phenomenon for the special case of solid spheres reveals that the image, to a good approximation, corresponds to a section of the sphere that is parallel to the azimuthal plane and at a standoff distance from it. The distance increases with the angle that the normal to the surface forms relative to the azimuthal plane while it decreases as the velocity contrast between ice and the material of the sphere decreases. While this property is not expected to hold for more complex surfaces, the ray-based framework used in this study is applicable to more general surface configurations and can be used to correlate the images to the structure of the solid. These findings are relevant to the inspection of metallic components with complex geometry which represents a long-standing challenge in the field of nondestructive testing.

Driven by the applications of advanced manufacturing technologies which enable complex designs, the nondestructive evaluation of damage in complex structures is playing an increasingly important role across various industries. The local defect resonance (LDR) has demonstrated greater applicability to defects in complex thin-walled structures than traditional methods. However, existing LDR-based methods suffer from the low accuracy in the quantitative evaluation of defect owing to the difficulty in determining the defect boundary. A method based on the frequency and attenuation of LDR is proposed in this investigation to quantify the diameter and thickness of circular defects simultaneously using the genetic algorithm. In this method, the reflections of guided ultrasonic waves at defect boundaries are analyzed using a normal mode expansion method, and thereby the relations between the FBH parameters (i.e., diameter and thickness) and LDR attributes (i.e., the frequency and attenuation rate) are obtained. On this basis, a method based on a genetic algorithm is proposed to inversely determine the defect parameters using the LDR attributes. The proposed method is validated through numerical investigation and experimental evaluations of a series of flat bottom holes in plate structures. The proposed method enhances the accuracy and efficiency for the quantitative evaluation of defects in complex structures, advancing the application of LDR-based nondestructive evaluation techniques and providing basis for developing structural health monitoring techniques using LDR.

Acoustic holography, which reconstructs desired target acoustic fields by precisely controlling the phase distribution of acoustic wavefronts, holds significant promise for applications such as acoustic manipulation. However, the precise modulation of acoustic field distributions via acoustic holography to construct multifocal fields with controllable acoustic intensity ratios remains insufficiently explored. To address this limitation, this study proposes a Physics-Informed Artificial Intelligence-based Angular Spectrum method (AIAS), which deeply integrates the physical model of angular spectrum propagation into the neural network training process. Combined with a specifically designed Target-Area-Weighted Mean Squared Error loss function, AIAS establishes an explicit optimization link between the phase distribution and the amplitude error in the target region during the inverse design process. Results demonstrate that acoustic fields reconstructed by AIAS exhibit more concentrated and uniform pressure distributions (average pressure improved from 262 ± 15 kPa to 276.4 ± 5.6 kPa), providing stable acoustic fields for particle assembly. Importantly, by controlling the phase gradient distribution, AIAS successfully constructs asymmetric acoustic fields with a 2:1 intensity ratio between two focal points. The exceptional amplitude modulation capabilities of AIAS represent a key technological breakthrough for achieving more precise and personalized transcranial focused ultrasound therapy.

Guided wave phased arrays, which use multiple sensors in compact patterns to perform damage imaging through phase delays, have garnered significant interest for the rapid inspection of large composite panels. Previous phased arrays typically used large, wired ultrasonic transducers attached to composites, limiting array reconfigurability and preventing contactless inspection from a distance. This study presents a fully noncontact guided wave phased array imaging approach, which utilizes a dual laser-based guided wave generation and sensing system, namely a pulsed laser-scanning laser Doppler vibrometer (PL-SLDV) system, along with synthetic phased array beamforming and wavefield analysis. The PL-SLDV system employs a Q-switched PL module to generate nanosecond laser pulses that excite ultrasonic guided waves through the thermoelastic effect. To ensure consistent laser-to-ultrasound energy conversion across different composites and prevent potential thermal damage to composites, the laser pulses are directed onto a thin aluminum patch bonded on the composite. The SLDV acquires guided wave signals based on the Doppler effect, and its integrated galvo mirrors can quickly steer laser beam directions to scan a composite plate, thereby acquiring guided wave signals at various array points. Time/phase delays are then applied to the acquired signals through post-processing for synthetic phased array beamforming. To generate inspection images using the acquired wave signals, an improved delay-and-sum (DAS) imaging algorithm is introduced. It uses adaptive weighting factors and incorporates phase delay and back-propagation phase shift, accounting for the frequency- and direction-dependent dispersion relation, to overcome the dispersion effect and directional dependency of waves in anisotropic materials. Moreover, the fusion of phased array imaging and a wavefield analysis approach, which can extract frequency-wavenumber dispersion relations from experimental wavefields, enables our phased array method to perform damage imaging without requiring prior knowledge of composite properties, such as mechanical properties or theoretical dispersion curves. Additionally, the noncontact wave generation/acquisition feature of our PL-SLDV system allows for inspecting composites from a distance and easily constructing phased arrays with different patterns. Proof-of-concept experiments demonstrate that multiple defects in different directions can be successfully detected. Additionally, this study reveals that PL-generated guided waves can contain multiple modes, such as A₀, S₀, SH₀, A₁, S₁, and SH₁ modes, offering valuable insights for researchers interested in using PL-generated guided waves.