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Ultrasound Imaging and Sensing for Nondestructive Testing

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 20 March 2025 | Viewed by 7898

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Special Issue Editors

Dr. Haoran Jin

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Guest Editor

Institute of Mechatronic Control Engineering, Zhejiang University, Hangzhou, China
Interests: robotic ultrasound imaging; ultrasonic nondestructive testing; medical ultrasound

Dr. Zesheng Zheng

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Guest Editor

Institute of Microelectronics, Agency for Science, Technology and Research, Singapore 138634, Singapore
Interests: ultrasound imaging; photoacoustic imaging; optical coherence tomography; non-contact vibration measurement

Dr. Siyu Liu

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Guest Editor

School of Science, Nanjing University of Science and Technology, Nanjing, China
Interests: photoacoustic imaging

Special Issue Information

Dear Colleagues,

In recent years, there has been rapid development in non-destructive testing technology for ultrasound imaging with robots and automation systems. This technology has expanded the application scope of ultrasound testing, from non-destructive testing of products in the fabrication process to in-service equipment inspection. However, the involvement of robots and automation systems has also raised higher technical requirements for ultrasound imaging, including imaging modes, detection accuracy, and efficiency. This Special Issue will explore various new robot-assisted and automated ultrasound imaging systems, related theories and algorithms for automated ultrasound imaging and testing, and ultrasound imaging technology for various non-destructive testing applications. Topics of interest include, by are not limited to, the following:

Ultrasound imaging and signal processing technology;
Automated ultrasound imaging technology and systems;
Robot-assisted ultrasound imaging and testing technology and systems;
Robot-assisted positioning, navigation, and ultrasound testing technology;
Other related automation and robot-assisted non-destructive testing technologies.

Both review articles and original research papers associated with ultrasonic systems, robots and automated inspection systems, ultrasonic sensors/transducers, and their applications in non-destructive testing are solicited. There is a particular interest in papers concerning techniques of ultrafast ultrasound imaging, three-dimensional ultrasound imaging, underwater ultrasound imaging, and their applications for non-destructive testing.

Dr. Haoran Jin
Dr. Zesheng Zheng
Dr. Siyu Liu
Guest Editors

Manuscript Submission Information

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Keywords

ultrasound imaging
non-destructive testing
automation testing system
robot-assisted testing system
laser ultrasonic imaging

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Published Papers (6 papers)

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Research

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20 pages, 10825 KiB

Open AccessArticle

Investigation of the Zero-Frequency Component of Nonlinear Lamb Waves in a Symmetrical Undulated Plate

by Xiaoqiang Sun and Guoshuang Shui

Sensors 2024, 24(15), 4878; https://doi.org/10.3390/s24154878 - 27 Jul 2024

Cited by 1 | Viewed by 574

Abstract

When an ultrasonic pulse propagates in a thin plate, nonlinear Lamb waves with higher harmonics and a zero-frequency component (ZFC) will be generated because of the nonlinearity of materials. The ZFC, also known as the static displacement or static component, has its unique application on the evaluation of early-stage damages in the elastic symmetrical undulated plate. In this study, analysis of the excitation mechanism of the ZFC and the second harmonic component (SHC) was theoretically and numerically investigated, and the material early-stage damage of a symmetrical undulated was characterized by studying the propagation of nonlinear Lamb waves. Both the ZFC and SHC can be effectively employed in monitoring the material damages of the undulated plate in its early stage. However, several factors must be considered for the propagation of the SHC in an undulated plate because of the geometric curvature and interference between the second harmonics during propagation, preventing efficient application of this technique. If the fundamental wave can propagate in the plate regardless of the plate boundary conditions, an accumulative effect always exists for the ZFC in a thin plate, indicating that the ZFC is independent of the structural geometry. This study reveals that the ZFC-based inspection technique is more efficient and powerful in characterizing the damages of a symmetrical undulated plate in the early stage of service compared to the second harmonic method. Full article

(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)

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15 pages, 4724 KiB

Open AccessArticle

On the Generalizability of Time-of-Flight Convolutional Neural Networks for Noninvasive Acoustic Measurements

by Abhishek Saini, John James Greenhall, Eric Sean Davis and Cristian Pantea

Sensors 2024, 24(11), 3580; https://doi.org/10.3390/s24113580 - 1 Jun 2024

Viewed by 955

Abstract

Bulk wave acoustic time-of-flight (ToF) measurements in pipes and closed containers can be hindered by guided waves with similar arrival times propagating in the container wall, especially when a low excitation frequency is used to mitigate sound attenuation from the material. Convolutional neural networks (CNNs) have emerged as a new paradigm for obtaining accurate ToF in non-destructive evaluation (NDE) and have been demonstrated for such complicated conditions. However, the generalizability of ToF-CNNs has not been investigated. In this work, we analyze the generalizability of the ToF-CNN for broader applications, given limited training data. We first investigate the CNN performance with respect to training dataset size and different training data and test data parameters (container dimensions and material properties). Furthermore, we perform a series of tests to understand the distribution of data parameters that need to be incorporated in training for enhanced model generalizability. This is investigated by training the model on a set of small- and large-container datasets regardless of the test data. We observe that the quantity of data partitioned for training must be of a good representation of the entire sets and sufficient to span through the input space. The result of the network also shows that the learning model with the training data on small containers delivers a sufficiently stable result on different feature interactions compared to the learning model with the training data on large containers. To check the robustness of the model, we tested the trained model to predict the ToF of different sound speed mediums, which shows excellent accuracy. Furthermore, to mimic real experimental scenarios, data are augmented by adding noise. We envision that the proposed approach will extend the applications of CNNs for ToF prediction in a broader range. Full article

(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)

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17 pages, 9152 KiB

Open AccessArticle

Ultrasonic Through-Metal Communication Based on Deep-Learning-Assisted Echo Cancellation

by Jinya Zhang, Min Jiang, Jingyi Zhang, Mengchen Gu and Ziping Cao

Sensors 2024, 24(7), 2141; https://doi.org/10.3390/s24072141 - 27 Mar 2024

Cited by 1 | Viewed by 994

Abstract

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

(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)

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18 pages, 28755 KiB

Open AccessArticle

Full-Matrix Imaging in Fourier Domain towards Ultrasonic Inspection with Wide-Angle Oblique Incidence for Welded Structures

by Mu Chen, Xintao Xu, Keji Yang and Haiteng Wu

Sensors 2024, 24(3), 832; https://doi.org/10.3390/s24030832 - 27 Jan 2024

Cited by 1 | Viewed by 1075

Abstract

The total focusing method (TFM) has been increasingly applied to weld inspection given its high image quality and defect sensitivity. Oblique incidence is widely used to steer the beam effectively, considering the defect orientation and structural complexity of welded structures. However, the conventional TFM based on the delay-and-sum (DAS) principle is time-consuming, especially for oblique incidence. In this paper, a fast full-matrix imaging algorithm in the Fourier domain is proposed to accelerate the TFM under the condition of oblique incidence. The algorithm adopts the Chebyshev polynomials of the second kind to directly expand the Fourier extrapolator with lateral sound velocity variation. The direct expansion maintains image accuracy and resolution in wide-angle situations, covering both small and large angles, making it highly suitable for weld inspection. Simulations prove that the third-order Chebyshev expansion is required to achieve image accuracy equivalent to the TFM with wide-angle incidence. Experiments verify the algorithm’s performance for weld flaws using the proposed method with the transverse wave and the full-skip mode. The depth deviation is within 0.53 mm, and the sizing error is below 15%. The imaging efficiency is improved by a factor of up to 8 compared to conventional TFM. We conclude that the proposed method is applicable to high-speed weld inspection with various oblique incidence angles. Full article

(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)

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18 pages, 4261 KiB

Open AccessArticle

High-Precision Corrosion Detection via SH1 Guided Wave Based on Full Waveform Inversion

by Jiawei Wen, Can Jiang and Hao Chen

Sensors 2023, 23(24), 9902; https://doi.org/10.3390/s23249902 - 18 Dec 2023

Cited by 1 | Viewed by 1210

Abstract

Corrosion detection for industrial settings is crucial for safe and efficient operations. Due to its high imaging resolution, the guided–wave full–waveform inversion tomography technique has significant potential for corrosion detection of plate metals. Limited by the long wavelengths of A0 and S0 mode waves, this method exhibits inadequate detection resolution for the earlier shallow and small corrosion defects. Based on the relatively short wavelength characteristics of the SH1 mode wave, we propose a high–precision corrosion detection method via SH1 guided wave using the full waveform inversion algorithms. By conducting finite element simulations of ultrasonic–guided waves on aluminum plates with varying corrosion defects, a comparison was made to assess the detection precision across A0, S0, and SH1 modes. The comparison results showed that, whether for regular or irregular defects, the SH1 mode wave always exhibited higher imaging accuracy than the A0 and S0 mode waves for shallow and small–sized defects. The corresponding experiments were conducted on an aluminum plate with simple or complex defects. The results of the experiments reconfirmed that the full waveform inversion method using SH1 guided wave can effectively reconstruct the shape and size of small and shallow corrosion defects within aluminum plates. Full article

(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)

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Review

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31 pages, 8640 KiB

Open AccessReview

Coded Excitation for Ultrasonic Testing: A Review

by Chenxin Weng, Xu Gu and Haoran Jin

Sensors 2024, 24(7), 2167; https://doi.org/10.3390/s24072167 - 28 Mar 2024

Cited by 1 | Viewed by 2170

Abstract

Originating in the early 20th century, ultrasonic testing has found increasingly extensive applications in medicine, industry, and materials science. Achieving both a high signal-to-noise ratio and high efficiency is crucial in ultrasonic testing. The former means an increase in imaging clarity as well as the detection depth, while the latter facilitates a faster refresh of the image. It is difficult to balance these two indicators with a conventional short pulse to excite the probe, so in general handling methods, these two factors have a trade-off. To solve the above problems, coded excitation (CE) can increase the pulse duration and offers great potential to improve the signal-to-noise ratio with equivalent or even higher efficiency. In this paper, we first review the fundamentals of CE, including signal modulation, signal transmission, signal reception, pulse compression, and optimization methods. Then, we introduce the application of CE in different areas of ultrasonic testing, with a focus on industrial bulk wave single-probe detection, industrial guided wave detection, industrial bulk wave phased array detection, and medical phased array imaging. Finally, we point out the advantages as well as a few future directions of CE. Full article

(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)

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