Air-Coupled and Resonant Pulse-Echo Ultrasonic Technique

Development of non-contact foreign body imaging base on photoacoustic signal intensity measurement

BACKGROUND

It is challenging to visually identify tiny and concealed foreign objects within the body due to their small size and subcutaneous location while they can cause infections.

METHODS

A non-contact photoacoustic system based on Rosencwaig-Gersho photoacoustic theory and dual modulator method is developed for detecting foreign objects in meat.

RESULT

The experiments conducted validate the successful development of this measurement technique with 10 μm spatial resolution and its corresponding mathematical model, demonstrating an 11% Mean Absolute Percentage Error (MAPE) in comparison to the experimental results. Dual modulator successfully regulates laser energy at MPE limit.

CONCLUSION

The utilization of non-contact photoacoustic signal intensity measurements enables the identification of foreign objects within the body. Further, the application of mathematical modelling can validate the measurement outcomes. These findings serve as a foundation for creating an affordable and straightforward foreign body detector.

Prognosis methods of stress corrosion cracking under harsh environmental conditions

Stress corrosion cracking (SCC) under harsh environmental conditions still poses a significant challenge, despite extensive research efforts. The intricate interplay among mechanical, chemical, and electrochemical factors hinders the accurate prognosis of material degradation and remaining service life. Furthermore, the demand for real-time monitoring and early detection of SCC defects adds further complexity to the prognostication process. Therefore, there is an urgent need for comprehensive review papers that consolidate current knowledge and advancements in prognosis methods. Such reviews would facilitate a better understanding and resolution of the challenges associated with SCC under harsh environmental conditions. This work aims to provide a comprehensive overview of various prognosis methods utilized for the assessment and prediction of SCC in such environments. The paper will delve into the following sections: exacerbating harsh environmental conditions, non-destructive testing (NDT) techniques, electrochemical techniques, numerical modeling, and machine learning. This review is inclined to serve as a valuable resource for researchers and practitioners working in the field, facilitating the development of effective strategies to mitigate SCC and ensure the integrity and reliability of materials operating in challenging environments. Despite considerable research, stress corrosion cracking in harsh environments remains a critical issue, complicated by the interplay of mechanical, chemical, and electrochemical factors. This review aims to consolidate current prognosis methods, including non-destructive testing, electrochemical techniques, numerical modeling, and machine learning. Key findings indicate that while traditional methods offer limited reliability, emerging computational approaches show promise for real-time, accurate predictions. The paper also briefly discusses notable SCC failure cases to underscore the urgency for improved prognosis techniques. This work aspires to fill knowledge gaps and serve as a resource for developing effective SCC mitigation strategies, thereby ensuring material integrity in challenging operational conditions.

High-Frequency Ultrasonic Spectroscopy of Structure Gradients in Injection-Molded PEEK Using a Focusing Transducer

For high-performance thermoplastic materials, material behavior results from the degree of crystallization and the distribution of crystalline phases. Due to the less stiff amorphous and the stiffer and anisotropic crystalline phases, the microstructural properties are inhomogeneous. Thus, imaging of the microstructure is an important tool to characterize the process-induced morphology and the resulting properties. Using focusing ultrasonic transducers with high frequency (25 MHz nominal center frequency) enables the imaging of specimens with high lateral resolution, while wave propagation is related to the elastic modulus, density and damping of the medium. The present work shows experimental results of high-frequency ultrasonic spectroscopy (HF-US) applied to injection-molded polyether-ether-ketone (PEEK) tensile specimens with different process-related morphologies. This work presents different analysis procedures, e.g., backwall echo, time of flight and Fourier-transformed time signals, facilitating the mapping of gradual mechanical properties and assigning them to different crystalline content and morphological zones.

GHz ultrasonic sensor for ionic content with high sensitivity and localization

Sensing the ionic content of a solution at high spatial and temporal resolution and sensitivity is a challenge in nanosensing. This paper describes a comprehensive investigation of the possibility of GHz ultrasound acoustic impedance sensors to sense the content of an ionic aqueous medium. At the 1.55 GHz ultrasonic frequency used in this study, the micron-scale wavelength and the decay lengths in liquid result in a highly localized sense volume with the added potential for high temporal resolution and sensitivity. The amplitude of the back reflected pulse is related to the acoustic impedance of the medium and a function of ionic species concentration of the KCl, NaCl, and CaCl₂ solutions used in this study. A concentration sensitivity as high as 1 mM and concentration detection range of 0 to 3 M was achieved. These bulk acoustic wave pulse-echo acoustic impedance sensors can also be used to record dynamic ionic flux.

Imaging Diagnostics of Inside of a Building Wall Using Millimeter-Wave Reflectometer

Progress in microwave and millimeter-wave technologies has enabled advanced diagnostics for industrial applications. The transmission, reflection, scattering and radiation processes of electromagnetic waves are utilized as diagnostic principles. Specifically, the reflectometric method has gained importance in various applications due to the possibility of the high localization and accessibility of measurements, as well as the non-destructive nature of the systems. In this paper, radar reflectometers were applied to the measurement of the inside of a building wall, that is, the inspection of tile materials attached to a concrete wall. The measurement principle utilizes the phase interference effect of the reflected wave due to the multiple reflections between the two layers (Fabry–Perot effect). The results show the imaging inside the surface related to the peering condition between the tile and concrete wall, and the quantitative evaluation of the condition with non-destructive inspection.

Analysis of Air-Coupled Transducer-Based Elastic Waves Generation in CFRP Plates

In this paper, the analysis of non-contact elastic waves generation in carbon fiber reinforced-polymer (CFRP) plate was conducted. Full non-contact elastic waves generation and sensing methods were also analyzed. Elastic waves generation was based on an air-coupled transducer (ACT) while waves sensing was based on a laser Doppler vibrometer. The excitation frequency was equal to 40 kHz. An optimal ACT slope angle for the generation of elastic waves mode was determined with the aid of dispersion curves calculated by using a semi-analytical model. Due to the stack sequence in the composite plate (unidirectional composite), ACT slope angles were different for waves generation in the direction along and across reinforcing fibers direction. Moreover, experimental verification of the optimal ACT slope angles was conducted. It was possible to generate A₀ wave mode in the direction along and across the reinforcing fibers. Optimal angles determined using ACT were equal to 16° (along fibers) and 34° (across fibers). In the case of optimal angles, elastic waves amplitudes are almost two times higher than for the case of ACT oriented perpendicularly to the plate surface. Moreover, experimental results based on ACT showed that it was possible to generate the SH₀ mode in the direction across the fiber for optimal angles equal to 10°. Finally, based on the A₀ wave mode propagation, the process for localization of discontinuities was performed. Discontinuities in the form of additional mass simulating damage were investigated. A simple signal processing algorithm based on elastic wave energy was used for creating damage maps. Authors compared discontinuity localization for ACT oriented perpendicularly to the plate and at the optimal slope angle. The utilization of non-contact waves excitation at optimal ACT slope angles helped to focus the wave energy in the desired direction. Moreover, in this case, elastic waves with the highest amplitudes were generated.

Machine Learning-Based Optoacoustic Tissue Classification Method for Laser Osteotomes Using an Air-Coupled Transducer

BACKGROUND AND OBJECTIVES

Using lasers instead of mechanical tools for bone cutting holds many advantages, including functional cuts, contactless interaction, and faster wound healing. To fully exploit the benefits of lasers over conventional mechanical tools, a real-time feedback to classify tissue is proposed.

STUDY DESIGN/MATERIALS AND METHODS

In this paper, we simultaneously classified five tissue types-hard and soft bone, muscle, fat, and skin from five proximal and distal fresh porcine femurs-based on the laser-induced acoustic shock waves (ASWs) generated. For laser ablation, a nanosecond frequency-doubled Nd:YAG laser source at 532 nm and a microsecond Er:YAG laser source at 2940 nm were used to create 10 craters on the surface of each proximal and distal femur. Depending on the application, the Nd:YAG or Er:YAG can be used for bone cutting. For ASW recording, an air-coupled transducer was placed 5 cm away from the ablated spot. For tissue classification, we analyzed the measured acoustics by looking at the amplitude-frequency band of 0.11-0.27 and 0.27-0.53 MHz, which provided the least average classification error for Er:YAG and Nd:YAG, respectively. For data reduction, we used the amplitude-frequency band as an input of the principal component analysis (PCA). On the basis of PCA scores, we compared the performance of the artificial neural network (ANN), the quadratic- and Gaussian-support vector machine (SVM) to classify tissue types. A set of 14,400 data points, measured from 10 craters in four proximal and distal femurs, was used as training data, while a set of 3,600 data points from 10 craters in the remaining proximal and distal femur was considered as testing data, for each laser.

RESULTS

The ANN performed best for both lasers, with an average classification error for all tissues of 5.01 ± 5.06% and 9.12 ± 3.39%, using the Nd:YAG and Er:YAG lasers, respectively. Then, the Gaussian-SVM performed better than the quadratic SVM during the cutting with both lasers. The Gaussian-SVM yielded average classification errors of 15.17 ± 13.12% and 16.85 ± 7.59%, using the Nd:YAG and Er:YAG lasers, respectively. The worst performance was achieved with the quadratic-SVM with a classification error of 50.34 ± 35.04% and 69.96 ± 25.49%, using the Nd:YAG and Er:YAG lasers.

CONCLUSION

We foresee using the ANN to differentiate tissues in real-time during laser osteotomy. Lasers Surg. Med. © 2020 Wiley Periodicals LLC.