Piezoelectric micro-robots have gained considerable attention in rescue and medical applications due to their rapid response times and high positioning accuracy. In this paper, inspired by the human butterfly locomotion pattern, we propose a novel resonant four-legged piezoelectric micro-robot designed to achieve fast and efficient movement in complex and confined spaces. The robot utilizes the parallel piezoelectric bimorph as the driving unit, and its leg structure mimics the butterfly motion. By employing asymmetric driving forces, the robot can achieve multi-directional movement. A dynamic model of the robot is developed, and the stress and motion characteristics are analyzed. The finite element method (FEM) is applied to optimize the structural parameters and determine the robot's optimal operating frequency. Finally, the prototype of the piezoelectric robot is constructed, and its performance is evaluated. The results show that, under an excitation voltage of 80 V, the robot achieves a maximum speed of 66.1 mm/s, can carry a load of up to 100 g, and withstand a maximum drag force of 15.3 mN. The robot demonstrates sub-micron resolution, excellent environmental adaptability, and precise rotational capabilities, making it suitable for tasks such as exploration, mapping, and sampling in constrained environments.

Corrosion is a major threat in the aeronautic industry, both in terms of safety and cost. Efficient, versatile, and cost affordable solutions for corrosion monitoring are thus needed. Ultrasonic Lamb Waves (LW) appear to be very efficient for corrosion monitoring and can be made cost effective and versatile if emitted and received by a sparse array of piezoelectric elements (PZT). A LW solution relying on a sparse PZT array and allowing to monitor µm-sized corrosion pit growth on stainless 316L grade steel plate is here evaluated. Experimentally, the corrosion pit size is electrochemically controlled by both the imposed electrical potential and the injection of a corrosive NaCl solution through a capillary located at the desired pit location. In parallel, the corrosion pit growth is monitored in-situ every 10 s by sending and measuring LW using a sparse array of 4 PZTs bonded to the back of the steel plate enduring corrosion. As a ground truth information, the corrosion pit volume is estimated as the dissolved volume balancing the electronic charges exchanged during corrosion. The corrosion pit radius is additionally checked post-experiment precisely with an optical measurement. Measured LW signals are then post-processed in order to compute a collection of synthetic damage indexes (DIs). After dimension reduction steps, obtained DI values correlates extremely well with the corrosion pit radius. Using a linear model relating those DI values to corrosion pit radius, it is demonstrated that corrosion pit from 30 µm to 150 µm can be reliably detected, located, and their upcoming size extrapolated. Two independent experiments were achieved in order to ensure the repeatability of the proposed approach. LW managed by a sparse PZT array thus appears to be reliable and efficient to monitor growth of µm-sized corrosion pits on 316L steel plates. If embedded in aeronautical structure, such an approach could be a versatile and cost-effective alternative to actual non-destructive maintenance procedures that are time and manpower consuming.

The current key issues in applying acoustofluidics in engineering lie in the inflexibility of manufacturing processes, particularly those involving modifications to piezoelectric materials and devices. This leads to inefficient prototyping and potentially high costs. To overcome these limitations, we proposed a technique that is capable of prototyping acoustofluidic devices in a straightforward manner. This is achieved by simply clamping a printed circuit board (PCB) featuring interdigital electrodes (IDEs) onto a substrate coated with a piezoelectric thin film. By applying appropriate clamping force between the PCB and the substrate, one can effectively generate surface acoustic waves (SAWs) along the surface of the substrate. This approach simplifies the prototyping process, reducing the complexity and fabrication time. The clamping mechanism allows for easy adjustment and optimization of the SAW generation, enabling fine-tuning of the fluid and particle manipulation capabilities. Furthermore, this method allows for customizable interdigital transducers (IDTs) by 'patterning' IDEs on thin-film piezoelectric substrates (such as ZnO/Al and ZnO/Si) with various anisotropy orientations. This facilitates the on-demand generation of wave modes, including A0 and S0 Lamb waves, Rayleigh waves, and Sezawa waves. One notable advantage of this method is its capability to rapidly test acoustic wave patterns and performance on any substrate, offering a fast and streamlined approach to assess acoustic behaviors across diverse materials, thereby paving the way for efficient exploration of novel materials in SAW technology.

This work offers an ultrasonic structural health monitoring (SHM) approach for assessing the defects located on the same surface and at one side of piezoelectric ultrasonic transducer array. It is based on the analysis of ultrasonic bulk wave travelling in the thickness direction obtained from an enhanced full-skip configuration of the time-of-flight diffraction (TOFD) technique. In contrast to existing TOFD setup only considering the direct paths between the ultrasonic transducer and defect, our ultrasound monitoring configuration involves twice reflected ultrasonic bulk wave (TRBW). The TRBW travels following the propagation route from an ultrasonic transmitter located at the same side of the defect initiated, the backwall, the defect tip, the backwall again and finally to the same or another ultrasonic transducer. Both theoretical analyses and experimental validations have been conducted in our study. A simplified algorithm for efficient detection and mapping the growth of a surface defect in an aluminum alloy block has been demonstrated with an incremental surface defect growth starting from 2.80 mm in depth, in which conformable direct-write ultrasonic transducers (DWT) made of in-situ piezoelectric coating are implemented. Our approach provides an ultrasonic method for effective monitoring the near surface defects with the ultrasonic transducers conveniently implemented on the same surface and at the same side of the defects.

Recently, significant research efforts have been made to enhance ultrasonic testing (UT) by employing artificial intelligence (AI). However, collecting an extensive amount of labeled data across various testing environments to train the AI model poses significant challenges. Moreover, conventional UT typically focuses on detecting deep-depth defects, which limits the effectiveness of such methods in detecting near-surface defects. To this end, this paper proposes a novel near-surface defect detection method for ultrasonic testing that can be employed without collecting labeled data. We propose a self-supervised anomaly detection model that incorporates domain knowledge. First, synthetic faulty samples are generated by fusing the measured UT signals with the back-wall UT reflection signals, to simulate real faulty features. Unlike the CutPaste method used for computer vision applications, this synthesis method adds the back-wall echo signal to random locations by incorporating the physical principles of the superposition of ultrasonic signals. Next, a de-anomaly network is devised to isolate subtle defect features within the measured UT signals. The presence of defects was determined using the three-sigma rule of the mean absolute value of the residual output. The defect depth is determined by a time-of-flight calculation from the residual output. The effectiveness of the proposed method was evaluated through the UT of aluminum blocks with near-surface defects of varying depths under different surface conditions. Both qualitative and quantitative comparison studies demonstrated that the proposed method outperformed existing methods in detecting the presence and depth of near-surface defects.

This paper reports on an acoustic emission (AE) sensor based on relaxor ferroelectric single crystal (RFSC) transduction. The sensor crystal is arranged into a Linear Array for Modal Decomposition and Analysis (LAMDA), with the sensor interrogated by a bespoke high-bandwidth instrument. The efficacy of RFSC LAMDA sensors is showcased through a series of comparative experiments, which include the simultaneous acquisition of pencil lead break (PLB) AEs in a 1.6 mm thick aluminium plate using RFSC LAMDA, a wideband commercial sensor, and laser vibrometry. Subsequent modal decomposition and analysis of the PLB AE signals, as detected by RFSC LAMDA, identified the guided wave modes below 1.4 MHz. Furthermore, it was found that RFSC LAMDA exhibits, on average, 26.6 times greater improvement in sensitivity compared with polyvinylidene fluoride LAMDA variant with near-identical geometry.

A novel methodology is introduced for the computation of stress-induced surface acoustic wave velocity shifts in piezoelectric resonators including quartz, lithium niobate and langasite resonators. The numerical framework has been verified through a comparative analysis of experimental and Finite Element Method (FEM) results for quartz resonators. This approach introduces the combined capabilities of COMSOL Multiphysics and MATLAB, facilitated by LiveLink, to systematically calculate all parameters contributing to the perturbation integral. The findings have a better accuracy using the LiveLink methodology in this study compared to prior approaches that rely on average stress and strain calculations in the central point of the resonator. Moreover, the utilization of LiveLink not only enhances accuracy but also establishes MATLAB as a fundamental software platform for interfacing with COMSOL Multiphysics. The proposed approach in this paper can extend to complex strain sensors or investigations into the influence of temperature and imbalanced loading effects in future research endeavors. Furthermore, the LiveLink approach introduced herein can be extended to optimize crystal orientation and identify premium wave directions, thereby contributing to the enhanced design of Surface Acoustic Wave (SAW) resonators. This innovative methodology is used to advance the understanding and application of stress-induced velocity shifts in SAW devices, presenting future developments in sensor technologies and resonator designs. © 2024 Elsevier Science. All rights reserved.

This paper presents a novel approach utilizing nonlinear ultrasonic guided waves for the detection and evaluation of high-cycle fatigue damage in aluminum alloy plates. Through high-cycle fatigue testing, specimens with varying degrees of fatigue damage were created and evaluated using ultrasonic-guided wave measurement technology. The integration of time-frequency analyses effectively reduced the impact of wave dispersion and resonance effects, establishing a reliable operational frequency bandwidth. The results identified a positive correlation between the amplitude of odd harmonic components caused by hysteresis nonlinearity and fatigue crack length, while an inverse correlation was observed with specimen resonance frequency. The results confirm the high sensitivity and accuracy of this approach for early fatigue damage detection, offering a significant advancement in the non-destructive evaluation of engineering structures and a foundation for structural failure prevention.

Surface acoustic waves have emerged as one of the potential candidates for the development of next-generation wave-based information and computing technologies. For practical devices, it is essential to develop the excitation techniques for different types of surface acoustic waves, especially at higher microwave frequencies, and to tailor their frequency versus wave vector characteristics. We show that this can be done by using ultrashort laser pulses incident on the surface of a multilayer decorated with a periodic array of metallic nanodots. Specifically, we study surface acoustic waves in the dielectric substrate Si/SiO decorated with a square lattice of thin NiFe (Py) dots. Using a femtosecond laser-based optical pump-probe measurement, we detect a number of high-frequency phononic modes. By performing finite element simulations, we identify them as Sezawa modes from the second and third Brillouin zone in addition to the modes confined within the Py dots. The frequency of the Sezawa modes strongly depends on the period of the Py dots and varies in the range between 5 to 15 GHz. Both types of waves cover the same frequency range for Py dots with period less than 400 nm, providing a promising system for magnetoelastic studies.

Finite element computations offer ways to study the behavior of ultrasonic waves in polycrystals. In particular, the simulation of plane waves propagation through small representative elementary volumes of a microstructure allows estimating velocities and scattering-induced attenuation for an effective homogeneous material. Existing works on this topic have focused mainly on longitudinal waves. The approach presented here relies on generating periodic samples of microstructures in order to accommodate both longitudinal and shear waves. After some discussion on the parametrization of the simulations and the numerical errors, results are shown for several materials. These results are compared to an established theoretical attenuation model that has been adapted to use a fully analytical expression of the two-point correlation function for the polycrystals of interest, and to use velocities corresponding to different reference media. Promising comparisons are obtained for both longitudinal and shear waves when using more representative media, obtained through Hill averaging or a self-consistent approach. This illustrates how the numerical method can assist in developing and validating analytical models for elastic wave propagation in heterogeneous media.

The main focus of this work is the echogenicity of a 3D-printed synthetic composite material that mimics the acoustic properties of cardiac biological tissues to provide ultrasound images similar to those obtained during interventional cardiology procedures. The 3D-printed material studied is a polymer-based composite with a matrix-inclusion microstructure, which plays a critical role in ultrasound response due to ultrasound-microstructure interaction at the involved medical echography wavelengths. Both numerical simulations and experimental observations are carried out to quantitatively establish the relationship between the 3D-printed microstructure and its ultrasonic echogenicity, considering different microstructure characteristics, namely area fraction and size of the inclusion, and its actual printed shape. A numerical evaluation based on finite element modeling is carried out to characterize the acoustic properties of the 3D-printed synthetic tissue: phase velocity, attenuation coefficient, and B-mode ultrasound images. Moreover, a morphological experimental study of the shape of the real 3D-printed inclusions is carried out. It shows a significant deviation of the final printed inclusions compared to the input spherical shape delivered to the 3D printer. By simulating and comparing numerically generated microstructures and 3D-printed real microstructures, it is shown that the actual shape of the inclusion is significant in the scattering of the ultrasonic wave and the echogenicity of the printed material.

The vibration and electrical characteristics of transducer is determined by material coefficients and geometry, with material coefficients being susceptible to factors including frequency, pressure, and temperature, which leads to poor repeatability of transducer characteristics. Consequently, it is challenging to provide an accurate theoretical model to predict the characteristics based on the current material coefficients. To achieve a more accurate transducer model, a measurement method is proposed based on the mapping between material coefficients and transducer characteristic parameters to obtain accurate coefficients under working conditions with simple equipment and lower costs. The mapping is analyzed based on the transducer model, identifying five key coefficients. An iterative optimization method is then developed to measure these coefficients. Additionally, the genetic algorithm (GA) method is utilized for cross-checking. Transducers made from seven different materials and with varying lengths are measured, and the coefficients are obtained by both methods. With the obtained coefficients, the vibration and electrical characteristics of multi-material transducers is predicted and found to be in good agreement with the measured values, validating the transducer model and the coefficient measurement method. These coefficients are then compared with results obtained from a dynamic mechanical analyzer (DMA) and reference values. The results demonstrate that theoretical coefficients obtained by the proposed method lead to more accurate predictions for the vibration and electrical characteristics compared to those obtained from the DMA and reference values. Furthermore, the influence of frequency on the coefficients is studied by the method. The iterative method and GA method are compared in terms of their relative errors.

High-density polyethylene (HDPE) is extensively utilized across various industries, including nuclear power, primarily for its exceptional properties. However, there are challenges with traditional linear ultrasound imaging systems due to the significant thicknesses and the highly attenuative of HDPE. High-frequency carrier waves can offer better imaging resolution but also suffer higher acoustic attenuation, which limits the propagation distance of primary longitudinal waves (PLW) and makes it difficult to detect defects within thick HDPEs. On the other hand, using low-frequency PLW for defect detection presents challenges in resolution despite lower attenuation and longer propagation distances. This study proposes a defect imaging method for HDPEs by using quasi-static components (QSC) generated along with high-frequency fundamental wave propagation because of the nonlinear effect. The QSC has the advantage of low attenuation because its carrier frequency is zero, which can propagate a long distance in a high acoustic attention medium like HDPE. A nonlinear ultrasonic imaging approach combining the QSC and synthetic aperture focusing technique is proposed for defect imaging in HDPEs. Experiments on HDPEs with single and multiple defects are conducted to verify the performance of the proposed method. For comparison, the imaging results using traditional linear ultrasounds with high (2.5 MHz) and low (0.5 MHz) carrier frequencies are also provided. The results show the proposed method has better imaging performance over traditional linear ultrasound imaging methods for defect defections in high acoustic attention medium.

A novel Signal Processing algorithm based on the combination of a Wavelet Transform Analysis and Image Processing techniques is designed for assessing the delamination detectability of Lamb Waves generated with an innovative fully non-contact system in CFRP plates. Several Damage Indexes are extracted from the wavefields in spatial-time-frequency domain and plotted as surface cartographies to visualise their ability to size and localise artificial delaminations. Results show that the algorithm is efficient for characterising the waves propagation and that sophisticated Image comparison indexes show better ability to detect the artificial defects and to recognise healthy zones despite signal measurement and calculation uncertainties.

Temperature is an important factor influencing the results of non-destructive acoustoelastic measurements of the internal stress in objects like bolts owing to its impact on the elastic modulus of the material. However, conventional methods that seek to obtain the temperature field of the measurement object independently suffer from high complexity and low accuracy. The present work addresses this issue by developing a method that eliminates the influence of temperature on the acoustoelastic measurements of stress in bolts based on the time interval between the head and coda waves of ultrasonic signals. The origin of coda waves in rod-shaped objects is investigated theoretically, and this understanding is applied for analyzing the relationship between the temperature and internal stress of the object and the time interval between the head and coda waves of ultrasonic signals. The analysis demonstrates that the observed time interval is related to temperature and stress in accordance with a linear relationship with the velocity of the longitudinal wave and the rod diameter. Finally, the obtained relationship is applied within an acoustoelastic measurement model to eliminate the influence of temperature from the measurement results.

This study aimed to investigate the effects of internal moisture migration and subsequent drying-shrinkage-induced micro-cracking in concrete on diffuse ultrasound, through a series of experiments that comprised multiple drying and rewetting cycles carried out over the long-term. Cyclic drying and wetting phenomena in concrete were physically established following a predefined protocol and were traced measuring the mass change of specimens. Diffuse-wave tests were conducted using a pair of PZT patches bonded to cylindrical specimens, which acted as the ultrasonic transmitter and receiver in the range of 250-550 kHz. The results present that measured diffuse-wave parameters, diffusivity and dissipation, showed distinct varying and cyclic behaviors to drying and wetting processes, but they did not recover their original values in the saturated condition, revealing possible micro-cracking damage caused by the drying process, which should be understood to improve the reliability of diffuse ultrasound measurements in concrete subjected to environmental changes.

Ultrasound computed tomography (USCT) has emerged as a promising platform for imaging tissue properties, offering non-ionizing and operator-independent capabilities. In this work, we demonstrate the feasibility of obtaining quantitative images of multiple acoustic parameters (sound speed and impedance) for soft tissues using full waveform inversion (FWI), which are justified with both numerical and experimental cases. A 3D reconstruction based on a series of 2D slice images is presented for the experimental case of ex vivo soft tissues. To improve the robustness of the reconstruction process, a hierarchical FWI strategy is adopted, gradually iterating from low to high frequencies. In parallel, we employ a graph-space optimal transport misfit function, avoiding convergence into local minima and minimizing inversion artifacts caused by skin-related supercritical reflections. Our method first carries out sound speed inversion based on transmitted waves in the low and middle frequency bands, and then uses all types of waves in the high frequency band for simultaneous inversion of both sound speed and impedance. Compared to conventional strategies, the proposed approach can accurately reconstruct physical models consistent with the actual soft tissue sample. These high-resolution ultrasound images of acoustic parameters are promising to allow for quantitative differentiation among different types of tissues (e.g., muscles and fats). These results have significant implications for advancing our understanding of tissue properties and for potentially contributing to disease diagnosis through USCT, which is a flexible and cost-effective alternative to X-ray computed tomography or magnetic resonance imaging at no significant sacrifices for resolution.

Ultrasonic detection technique (UDT) serves as a pivotal method for monitoring aircraft icing conditions. However, the inherently porous and irregular shape of atmospheric ice leads to a pronounced attenuation of ultrasonic wave energy during propagation. Current ultrasonic transducers (UTs) fall short of meeting the requisite sensitivity and depth parameters for effective detection. This study proposes an innovative focused ultrasonic transducer (FUT) designed to extend the range of ice detection capabilities. Constructed using a 1-3 piezoelectric composite configuration, this FUT is characterized by its flexibility and slender profile. The focusing effect was accomplished through a deliberate bending mechanism. The FUT demonstrates its efficacy in detecting ice on aluminium skin surfaces. Furthermore, we validated the focusing effect and conducted a thorough optimization process. A comparative analysis between the FUT and traditional planar UTs revealed that the FUT enhances detection energy by approximately 30%, while also nearly doubling the detection range for glaze ice. These findings underscore the FUT's promising potential for applications in the detection of substantial ice.

Quasi-phasematched mixing processes of acoustic waves via second-order nonlinearity are analyzed with two perfectly guided waves generating a leaky wave. The efficiency of such processes is quantified by an acoustic nonlinearity parameter (ANP), defined as the linear growth rate of the leaky wave's amplitude in the initial stage of its spatial evolution. Two approximate ways of estimating the ANP of such processes are suggested. The first starts from a stationary solution of the equation of motion and boundary conditions for the displacement field, obtained within perturbation theory. This approach requires the solution of a near-singular linear system of equations. The second is based on the resonant state expansion of the displacement field generated in the mixing process. It allows to express the ANP in the form of an overlap integral, requiring normalization of the displacement field associated with the leaky wave. For leaky output waves with a high degree of localization at the waveguide, both methods yield results in good agreement, as demonstrated for an example system with generalized (2D) plate modes. The first approach has also been applied to finite element calculations of the ANP for nonlinear mixing processes of (1D) edge waves in an elastic plate with rigid faces.

This study investigates the application of Electrochemical Micromachining (ECMM) on magnesium alloy AZ31 using a hollow tool electrode. Magnesium alloys, particularly AZ31, are valued for their lightweight properties and strength-to-weight ratio but pose challenges in precision machining due to their high reactivity and susceptibility to corrosion. Utilizing a hollow tool electrode in ECMM offers potential advantages in precision and control, crucial for micro-scale manufacturing applications. This research focuses on studying the effect of process parameters such as electrolyte composition, voltage, and duty cycle to achieve high-quality micro holes. Experimental results demonstrate the effects of these parameters on machining speed and overcut. Findings indicate that the use of a hollow tool electrode significantly improves the hole geometry and surface integrity of the machined features, making ECMM a viable technique for the micromachining of magnesium alloys. The experimental outcome shows that the maximum MS of 0.439 μm/s was noted with 156 OC. The machining was enhanced by 12 % when compared to traditional submerged machining with a solid tool.

Quasi-static elastography (QSE) is a well-established technique used in medical imaging, where ultrasound data is collected both, before and after applying a slight compression on a tissue. This data is then analyzed to create image frames that reveal the stiffness parameter of the underlying tissue medium. Previous studies have focused on assessing how the Conventional Focused Beam (CFB) transmit method impacts the ultrasound elastography image quality. Recent studies have also shown an interest in synthetic aperture techniques like the Diverging Beam Synthetic Aperture Technique (DBSAT), due to its potential to enhance ultrasound image quality. However, its application in elastography has received limited attention. This paper introduces a new strategy of averaging low-resolution elastogram frames (LREA), obtained from DBSAT transmit method to improve the quality of elastography images. The CFB technique involves scanning the tissue line by line. In contrast, DBSAT is a synthetic aperture method that generates multiple low-resolution elastogram frames before combining them together to create a single high-quality image. In this research paper all the experimental studies were conducted on an agar-gelatin phantom, demonstrating the effectiveness of estimating elastograms from the low-resolution frame data of DBSAT transmit scheme and then summing them together to produce an elastogram with enhanced image quality. The results show a maximum improvement of 8 dB in the image quality metric of signal-to-noise ratio (SNR) as well as a 7 dB improvement in contrast-to-noise ratio (CNR) when comparing elastography images obtained by the proposed LREA method and the elastography images obtained by regular processing of the RF data acquired using the different methods of CFB and DBSAT.