Search Results (157)

To address the challenges of automatic detection caused by the variation of surface normal vectors in automotive steering knuckles, an automatic detection method based on ultrasonic phased array technology is herein proposed. First, a point cloud model of the workpiece was constructed using ultrasonic distance measurement, and Gaussian-weighted principal component analysis was used to estimate the normal vectors of the point cloud. By utilizing the normal vectors, water layer thickness during detection, and the incident angle of the sound beam, the probe pose information corresponding to the detection point was precisely calculated, ensuring the stability of the sound beam incident angle during the detection process. At the same time, in the trajectory planning process, piecewise cubic Hermite interpolation was used to optimize the detection trajectory, ensuring continuity during probe movement. Finally, an automatic detection system was set up to test a steering knuckle specimen with surface circumferential cracks. The results show that the point cloud data of the steering knuckle specimen, obtained using phased array ultrasound, had a relative measurement error controlled within 1.4%, and the error between the calculated probe angle and the theoretical angle did not exceed 0.5°. The probe trajectory derived from these data effectively improved the B-scan image quality during the automatic detection of the steering knuckle and increased the defect signal amplitude by 5.6 dB, demonstrating the effectiveness of this method in the automatic detection of automotive steering knuckles. Full article

Objectives: This study aimed to evaluate the efficacy of cleaning in minimally shaped mesial and oval distal canals of 3D models of mandibular molars, focusing on positive pressure irrigation, wireless and conventional passive ultrasonic irrigation (PUI), and diode laser (DL) at 980 nm. Methods: Forty-four 3D-printed resin models, based on eleven natural mandibular molars (each with mesial and distal canals), were divided into four groups (n = 11 per group) to evaluate different irrigation methods. A total of 22 mesial canals (size 20/.04) and 11 oval distal canals (size 25/.04) were analyzed per group. Each root canal was uniformly filled with an artificial hydrogel to simulate a biofilm mixture. Following this preparation, the specified irrigation techniques were applied to the respective groups. Quantitative evaluations of pre- and post-irrigation images were performed to assess the efficiency of tissue removal along the entire length of the canal and in the apical, middle, and coronal thirds. Results: The findings revealed no significant differences in the initial amount of tissue between the samples, indicating uniform filling. In the apical region of mesial canals, conventional PUI showed the highest cleaning efficiency (14.1% residual tissue), significantly outperforming the other methods (p < 0.05). Cordless PUI and DL also surpassed positive pressure irrigation, leaving 30.4% and 29.3% residual tissue, respectively, compared to 42.2% with positive pressure. In the middle third, all methods tested performed better than needle irrigation (p < 0.05), but there were no significant differences in the coronal third or over the full canal length. Distal oval canals showed no significant differences in cleaning effectiveness among methods. Conclusions: Although no single method was superior regarding the full canal length, supplementary techniques such as PUI and DL offer potential benefits over conventional irrigation methods, particularly in the apical third of the canal. Complementary approaches such as conventional PUI and diode laser at 980 nm showed superior cleaning efficiency, particularly in the apical third. These results suggest their integration could improve the effectiveness of cleaning in minimally instrumented mesial canals. Full article

An emerging alternative to conventional piezoelectric technologies, which continue to dominate the ultrasound medical imaging (US) market, is Capacitive Micromachined Ultrasonic Transducers (CMUTs). Ultrasound transducers based on this technology offer a wider frequency bandwidth, improved cost-effectiveness, miniaturized size and effective integration with electronics. These features have led to an increase in the commercialization of CMUTs in the last 10 years. We conducted a review to answer three main research questions: (1) What are the commercially available CMUT-based clinical sonographic devices in the medical imaging space? (2) What are the medical imaging applications of these devices? (3) What is the performance of the devices in these applications? We additionally reported on all the future work expressed by modern studies released in the past 2 years to predict the trend of development in future CMUT device developments and express gaps in current research. The search retrieved 19 commercially available sonographic CMUT products belonging to seven companies. Four of the products were clinically approved. Sonographic CMUT devices have established their niche in the medical US imaging market mainly through the Butterfly iQ and iQ+ for quick preliminary screening, emergency care in resource-limited settings, clinical training, teleguidance, and paramedical applications. There were no commercialized 3D CMUT probes. Full article

With the growth of global liquefied natural gas (LNG) demand, automation technology has become a key trend to improve the efficiency and safety of LNG handling. In this study, a novel automatic docking system is proposed which adopts a staged docking strategy based on a monocular camera for positioning and combines ultrasonic sensors to achieve multi-stage optimization in the fine docking stage. In the coarse docking stage, the system acquires flange image data through the monocular camera, calculates 3D coordinates based on geometric feature extraction and coordinate transformation, and completes the preliminary target localization and fast approach; in the fine docking stage, the ultrasonic sensor is used to measure the multidirectional distance deviation, and the fusion of the monocular data is used to make dynamic adjustments to achieve high-precision alignment and localization. Simulation and experimental verification show that the system has good robustness in complex environments, such as wind and waves, and can achieve docking accuracy within 3 mm, which is better than the traditional manual docking method. This study provides a practical solution for automated docking of LNG loading arms, which can significantly improve the efficiency and safety of LNG loading and unloading operations. Full article

Ultrasonic sensing may become a useful technique for distance measurement and object detection when optical visibility is not available. However, the research on detecting multiple target objects and locating their coordinates is limited. This makes it a valuable topic. Reflection signal data obtained from a single ultrasonic sensor may be just enough for the measurements of distance and reflection strength. On the other hand, if extracted properly, a scanned set of signal data by the same sensor holds a significant amount of information about the surrounding geometries. Evaluating this dataset from a single sensor scanning can be a perfect application for convolutional neural networks (CNNs). This study proposes an imaging technique based on a scanned dataset obtained by a single low-cost ultrasonic sensor. So that images are suitable for desired outputs in a CNN, a 3D printer is converted to an ultrasonic image scanner and automated to perform as a data acquisition system for the desired datasets. A deep learning model demonstrated by this work extracts object features using convolutional neural networks (CNNs) and performs coordinate estimation using regression layers. With the proposed solution, by training a reasonable amount of obtained data, 90% accuracy was achieved in the classification and position estimation of multiple objects with the CNN algorithm as a result of converting the signals obtained from ultrasonic sensors into images. Full article

Objectives: The aim of the present study was to examine the growth dynamics of the first sacral vertebra and its ossification center in the human fetus, based on their linear, planar, and volumetric parameters. Methods: The examinations were carried out on 54 human fetuses of both sexes (26 males and 28 females) aged 18–30 weeks of gestation, which had been preserved in 10% neutral formalin solution. Using CT, digital image analysis software, 3D reconstruction, and statistical methods, the size of the first sacral vertebra and its ossification center was evaluated. Results: The first sacral vertebra and its ossification center grew proportionately according to fetal weeks. Conclusions: The numerical data obtained from computed tomography and the growth patterns of the body of the first sacral vertebra and its ossification center may serve as age-specific normative intervals relevant for gynecologists, obstetricians, pediatricians, and radiologists during fetal ultrasound screening. Our findings on the growth of the body of the first sacral vertebra and its ossification center may be useful in daily clinical practice, particularly in ultrasonic monitoring of normal fetal growth and in screening for congenital defects and skeletal dysplasias. Full article

The predictive brain hypothesis suggests that perception can be interpreted as the process of minimizing the error between predicted perception tokens generated via an internal world model and actual sensory input tokens. When implementing working examples of this hypothesis in the context of in-air sonar, significant difficulties arise due to the sparse nature of the reflection model that governs ultrasonic sensing. Despite these challenges, creating consistent world models using sonar data is crucial for implementing predictive processing of ultrasound data in robotics. In an effort to enable robust robot behavior using ultrasound as the sole exteroceptive sensor modality, this paper introduces EchoPT (Echo-Predicting Pretrained Transformer), a pretrained transformer architecture designed to predict 2D sonar images from previous sensory data and robot ego-motion information. We detail the transformer architecture that drives EchoPT and compare the performance of our model to several state-of-the-art techniques. In addition to presenting and evaluating our EchoPT model, we demonstrate the effectiveness of this predictive perception approach in two robotic tasks. Full article

Piezoelectric composite materials, combining the advantages of both piezoelectric materials and polymers, have been extensively used in ultrasonic transducers. However, the pitch size of radial array ultrasonic transducers normally exceeds one wavelength, which limits their performance. In order to minimize grating lobes of current radial transducers and then increase their imaging resolution, a 2.5 MHz 1-3 composite radial array transducer with 64 elements and 600 μm pitch was designed and fabricated by combining flexible circuit board and using a bending-and-superposition method. All the array elements were connected and actuated via the customized circuit board which is thin and soft. The kerf size is set to be 1/3 wavelength. PZT-5H/epoxy 1-3 composite was used as an active material because it exhibits an ultrahigh electromechanical coupling coefficient (k_t = 0.74), a very low mechanical quality factor (Q_m = 11), and relatively low acoustic impedance (Z_c = 13.43 MRayls). The developed radial array transducer exhibited a center frequency of 2.72 MHz, an average −6 dB bandwidth of 36%, an insertion loss of 31.86 dB, and a crosstalk of −26.56 dB between the adjacent elements near the center frequency. These results indicate that the bending-and-superposition method is an effective way to fabricate radial array transducers by binding flexible circuit boards. Furthermore, the utilization of tailored flexible circuitry boards presents an effective approach for realizing reductions in crosstalk level (CTL). Full article

In a recent study using 3-D fullwave simulations, it was shown for a nonhuman primate model that a helmet-shaped 3D array of 128 transducer elements can be assembled for neurostimulation in an optimized configuration with the accommodation of an imaging aperture. Considering all acoustic losses, according to this study, for a nonhuman primate skull, the assembly of the proposed transducers was projected to produce sufficient focusing gain in two different focal positions at deep and shallow brain regions, thus providing sufficient acoustic intensity at these distinct focal points for neural stimulation. This array also has the ability to focus on multiple additional brain regions. In the work presented here, we designed and fabricated a single 15 mm diameter capacitive micromachined ultrasonic transducer (CMUT) element operating at 800 kHz central frequency with a 480 kHz 3 dB bandwidth, capable of producing a 190 kPa peak negative pressure (PNP) on the surface. The corresponding projected transcranial spatial peak pulse average intensity (I_SPPA) was 28 Wcm⁻², and the mechanical index (MI) value was 1.1 for an array of 128 of these elements. Full article

In ultrasonic nondestructive testing (NDT), accurately estimating the time of flight (TOF) of ultrasonic waves is crucial. Traditionally, TOF estimation involves the signal processing of a single measured waveform. In recent years, deep learning has also been applied to estimate the TOF; however, these methods typically process only single waveforms. In contrast, this study acquired fan-beam ultrasonic waveform profile data from 64 paths using an ultrasonic-speed computed tomography (CT) simulation of a circular column and developed a TOF estimation model using two-dimensional convolutional neural networks (CNNs) based on these data. We compared the accuracy of the TOF estimation between the proposed method and two traditional signal processing methods. Additionally, we reconstructed ultrasonic-speed CT images using the estimated TOF and evaluated the generated CT images. The results showed that the proposed method could estimate the longitudinal TOF more accurately than traditional methods, and the evaluation scores for the reconstructed images were high. Full article

This paper presents a study to accurately evaluate defects in concrete decks using ultrasonic pulse-echo signals. A reinforced concrete deck with void defects was designed and evaluated for validation, and a commercial ultrasonic pulse-echo (UPE) device was used to obtain the 2D images of the void defect inside the deck. The UPE image is based on the ultrasonic shear-wave test method and an extended synthetic aperture focusing technique (SAFT). To enhance the accuracy of the defect location in the SAFT imaging, the recorded A-scan data from UPE was analyzed using an advanced denoising approach and defect echo peak extraction, which are based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. The results demonstrated that the location and depth of the void defect in the deck can be accurately assessed by using the developed approach. The new method provides quantitative information of the anomalies inside the deck, which can be used to calibrate the qualitative images of UPC devices with the SAFT. Full article

Ultrasonic testing is widely used for defect detection in polymer composites owing to advantages such as fast processing speed, simple operation, high reliability, and real-time monitoring. However, defect information in ultrasound images is not easily detectable because of the influence of ultrasound echoes and noise. In this study, a stable three-dimensional deep convolutional autoencoder (3D-DCA) was developed to identify defects in polymer composites. Through 3D convolutional operations, it can synchronously learn the spatiotemporal properties of the data volume. Subsequently, the depth receptive field (RF) of the hidden layer in the autoencoder maps the defect information to the original depth location, thereby mitigating the effects of the defect surface and bottom echoes. In addition, a dual-layer encoder was designed to improve the hidden layer visualization results. Consequently, the size, shape, and depth of the defects can be accurately determined. The feasibility of the method was demonstrated through its application to defect detection in carbon-fiber-reinforced polymers. Full article

The effective detection of delamination defects, especially sub-millimeter delamination defects, in metal-clad plates is of great significance in improving product quality. In this work, the laser ultrasonic (LU) local resonance method is used to locate and characterize the sub-millimeter defects in stainless/carbon steel-clad plates. The influence of the delamination radius on the amplitude and resonant frequency of the laser ultrasound was investigated using 2D axisymmetric finite element (FE) simulations. The simulation results show that both the amplitude and the first resonance frequency (FRF) are effective features for detecting large-scale delamination defects, but the FRF is a better feature for detecting tiny delamination defects. A 304/Q235/304-clad plate specimen was made through a hot rolling bonding process, which contained a large number of self-forming delamination defects. The laser ultrasonic signals of different composite states collected in the experiment have good consistency with the simulated waveforms. The experimental results show that the laser ultrasonic local resonance method is a high-resolution imaging method, which can locate and characterize the sub-millimeter delamination defects in stainless/carbon steel-clad plates. Full article

Ultrasound is extremely efficient for wireless signal transmission through metal barriers due to no limit of the Faraday shielding effect. Echoing in the ultrasonic channel is one of the most challenging obstacles to performing high-quality communication, which is generally coped with by using a channel equalizer or pre-distorting filter. In this study, a deep learning algorithm called a dual-path recurrent neural network (DPRNN) was investigated for echo cancellation in an ultrasonic through-metal communication system. The actual system was constructed based on the combination of software and hardware, consisting of a pair of ultrasonic transducers, an FPGA module, some lab-made circuits, etc. The approach of DPRNN echo cancellation was applied to signals with a different signal-to-noise ratio (SNR) at a 2 Mbps transmission rate, achieving higher than 20 dB SNR improvement for all situations. Furthermore, this approach was successfully used for image transmission through a 50 mm thick aluminum plate, exhibiting a 24.8 dB peak-signal-to-noise ratio (PSNR) and a about 95% structural similarity index measure (SSIM). Additionally, compared with three other echo cancellation methods—LMS, RLS and PNLMS—DPRNN has demonstrated higher efficiency. All those results firmly validate that the DPRNN algorithm is a powerful tool to conduct echo cancellation and enhance the performance of ultrasonic through-metal transmission. Full article

The total focusing method (TFM) is often considered to be the ‘gold standard’ for ultrasonic imaging in the field of nondestructive testing. The use of matrix phased arrays as probes allows for high-resolution volumetric TFM imaging. Conventional TFM imaging involves the use of full matrix capture (FMC) for ultrasonic signals acquisition, but in the case of a matrix phased array, this approach is associated with a huge volume of data to be acquired and processed. This severely limits the frame rate of volumetric imaging with 2D probes and necessitates the use of high-end equipment. Thus, the aim of this research was to develop a novel design method for determining the optimal sparse 2D probe configuration for specific conditions of ultrasonic imaging. The developed approach is based on simulated annealing and involves implementing the solution of the sparse matrix phased array layout optimization problem. In order to implement simulated annealing for the aforementioned task, its parameters were set, the acceptance function was introduced, and the approaches were proposed to compute beam directivity diagrams of sparse matrix phased arrays in TFM imaging. Experimental studies have shown that the proposed approach provides high-quality volumetric imaging with a decrease in data volume of up to 84% compared to that obtained using the FMC data acquisition method. Full article