Recently, acoustic levitation for non-contact micro-particle manipulation has been attracting great interest in physical, biological, and medical applications. Among the state-of-the-art manipulation technologies, single beam acoustic tweezing exhibits advantages of providing stronger trapping force and deeper penetration depth in tissues, inducing less tissue damage, and a simple configuration involving only one device. However, particle trapping by the single beam acoustic tweezer could only be operated on a smooth two-dimensional substrate, which limits the potential for real applications. Here, we report an initial attempt to acoustically levitate an individual micro-particle stably in water and manipulate the levitated micro-particle arbitrarily two-dimensionally by simply employing a 60-MHz focused ring ultrasonic transducer. The proposed working mechanism agrees well with the phenomenon. This approach could not only acoustically levitate and manipulate a micro-particle on a culture dish and on a mylar film, but could also work properly in levitating and manipulating a micro-particle placed inside the polyimide tube. This simple and low-cost approach is extremely useful for effective non-contact micro-particle manipulation without having critical concerns on the substrate properties.

Defects or discontinuities are inevitable during the melting and consolidation process of metal additive manufacturing. Online inspection of microdefects during the processing of layer-by-layer fusion is urgently needed for quality control. In this study, the laser ultrasonic C-scan imaging system is established to detect the surface defects of selective laser melting (SLM) samples that have a different surface roughness. An autosizing method based on the maximum correlation coefficient and lag time is proposed to accurately measure the defect length. The influences of the surface roughness on the laser ultrasound signal-to-noise ratio distribution and defect sizing accuracy are also studied. The results indicate that the proposed system can detect notches with a depth of 50 µm and holes with a diameter of 50 µm, comparable in size to raw powder particles. The average error for the length measurement can reach 1.5% if the notch is larger than 2 mm. Meanwhile, the sizing error of a 1 mm length notch is about 9%. In addition, there is no need to remove the rough surface of the as-built SLM samples during the detection process. Hence, we propose that the laser ultrasonic imaging system is a potential method for online inspection of metal additive manufacturing.

This paper reported a method for designing monolithic acoustic holograms with consideration of both amplitude and phase modulation, which can be used for multifocal point beam forming by a single element ultrasonic transducer in the frequency of megahertz range. Mask-image-projection-based stereolithography 3D printing technology was induced to manufacture the complex hologram with a pixel resolution of 25 μm. A nine foci pattern and a letter U pattern acoustic field shown by a 2 MHz transducer and holograms were designed to validate the proposed designing method. Both the hydrophone testing and the simulation results indicated that the holograms designed by our method could form beam patterns accurately in the expected position.

Ultrasonic signal classification in nondestructive testing is of great significance for the detection of defects. The current methods have mainly utilized low-level handcrafted features based on traditional signal processing approaches, such as the Fourier transform, wavelet transform and the like, to interpret the information carried by signals for classification. This paper proposes an automatic classification method via a convolutional neural network (CNN) which can automatically extract features from raw data to classify ultrasonic signals collected of a circumferential weld composed of austenitic and martensitic stainless steel with internal slots. Experiments demonstrate that our method outperforms the traditional classifier with manually extracted features, achieving an accuracy rate of classification up to 0.982. Furthermore, we visualize the shape, location and orientation of defects with a C-scan imaging process based on classification results, validating the effectiveness of the results.

The accurate measurement of the prestress for bolt has been intensively investigated in recent years. Many research studies have been conducted to improve the accuracy of prestress measurement using ultrasound techniques; in particular, the real-time prestress of bolt can be obtained without the requirements to calibrate the original load when ultrasonic longitudinal and transverse waves are applied simultaneously. However, there are few studies that have focused on ultrasonic transducers that can generate longitudinal and transverse waves simultaneously. Furthermore, research on coatings deposited directly on the top of the bolts for the excitation of longitudinal and transverse waves has not been reported. ZnO coating is widely used for the ultrasonic transducer due to its excellent piezoelectric property and stable structure in high temperatures. Therefore, it is an outstanding candidate for the excitation of both longitudinal and transverse waves and has a good application prospect in the field of bolt prestress measurement by ultrasonic sound wave with high accuracy. In this paper, ZnO piezoelectric coatings were deposited on (100)-oriented Si substrates by radio frequency sputtering techniques. The morphology, structure, and echo signal characteristics of the coatings were characterized by SEM, AFM, XRD, and ultrasonic measurement instruments. The experimental results showed that Ar/O2 ratio and deposition position exhibited significant effects on the excitation waveform of the ZnO piezoelectric coating. When the Ar/O2 ratio reduced to 1:3, the coating could excite both transverse and longitudinal waves. However, when the deposition position gradually moved away from the sputtering center, the transverse wave gradually enhanced. The coating could excite a pure transverse wave when the sample was at the edge of the effective sputtering area, which showed that the type of the excitation wave and the relative intensity of each wave could be well controlled by the Ar/O2 ratio and deposition position. These research results have a good application prospect in bolt stress measurement.

A new method to measure the depth of subsurface defects in additive manufacturing components is proposed based on the velocity dispersion analysis of Lamb waves by the wavelet-transform of laser ultrasound. Firstly, the mode-conversion from laser-generated surface waves to Lamb waves caused by subsurface defects at different depths is studied systematically. Secondly, an additive manufactured 316L stainless steel sample with six subsurface defects has been fabricated to validate the efficiency of the proposed method. The measured result of the defect depth is very close to the real designed value, with a fitting coefficient of 0.98. The defect depth range for high accuracy measurement is suggested to be lower than 0.8 mm, which is enough to meet the inspection of layer thickness during additive manufacturing. The result indicates that the proposed method based on laser-generated ultrasound (LGU) velocity dispersion analysis is robust and reliable for defect depth measurement and meaningful to improve the processing quality and processing efficiency of additive/subtractive hybrid manufacturing.