2-D and 3-D Reconstruction Algorithms in the Fourier Domain for Plane-Wave Imaging in Nondestructive Testing

Ultrasonic Time-of-Flight Diffraction Imaging Enhancement for Pipeline Girth Weld Testing via Time-Domain Sparse Deconvolution and Frequency-Domain Synthetic Aperture Focusing

Ultrasonic TOFD imaging, as an important non-destructive testing method, has a wide range of applications in pipeline girth weld inspection and testing. Due to the limited bandwidth of ultrasonic transducers, near-surface defects in the weld are masked and cannot be recognized, resulting in poor longitudinal resolution. Affected by the inherent diffraction effect of scattered acoustic waves, defect images have noticeable trailing, resulting in poor transverse resolution of TOFD imaging and making quantitative defect detection difficult. In this paper, based on the assumption of the sparseness of ultrasonic defect distribution, by constructing a convolutional model of the ultrasonic TOFD signal, the Orthogonal Matching Pursuit (OMP) sparse deconvolution algorithm is utilized to enhance the longitudinal resolution. Based on the synthetic aperture acoustic imaging model, in the wavenumber domain, backpropagation inference is implemented through phase transfer technology to eliminate the influence of diffraction effects and enhance transverse resolution. On this basis, the time-domain sparse deconvolution and frequency-domain synthetic aperture focusing methods mentioned above are combined to enhance the resolution of ultrasonic TOFD imaging. The simulation and experimental results indicate that this technique can outline the shape of defects with fine detail and improve image resolution by about 35%.

An efficient ultrasonic wavenumber-domain plane wave imaging method towards the inspection of curved structures

Ultrasonic phased array testing is commonly employed for inspecting curved structures. Conventional plane wave imaging techniques, based on delay-and-sum in the time-domain, offer high image quality and inspection accuracy but suffer from low frame rates due to their high computational complexity. In this work, an efficient wavenumber-domain imaging method that combines non-stationary wavefield extrapolation and f-k migration is proposed for curved structure inspection. Special emission focal laws are designed to generate a sequence of steered plane waves through the curved interface. The raw data is then extrapolated to the top boundary of the region of interest, followed by f-k migration to reconstruct images with high time efficiency. Simulation and experimental evaluations demonstrate a time reduction by a factor of up to 32.24 compared to conventional time-domain plane wave image reconstruction with equivalent image quality, highlighting its potential for monitoring flaws in real-time.

Improved Coherent Plane-Wave Compounding Using Sign Coherence Factor Weighting for Frequency-Domain Beamforming

This study proposes a novel modified sign coherence factor (SCF) weighting adapted to the frequency-domain (FD) beamforming for ultrasound plane-wave imaging to achieve a high frame rate and better image quality. First, before beamforming, the sign components were extracted from the radiofrequency signals of aperture data. Second, the modified SCF was established using the FD beamformed sign components. Finally, the FD beamformed image was weighted by the modified SCF. To assess the performance of the proposed modified SCF for FD beamforming, the resolution, contrast, computation complexity and execution time of the generated images were evaluated. The results revealed that the FD-SCF could significantly improve the computational load compared with the classic delay-and-sum SCF on the premise of equal image quality improvement. Therefore, high image quality and low computational load have been successfully combined under the proposed weighting method.

Circular statistics vector for improving coherent plane wave compounding image in Fourier domain

In this work, a circular statistics vector (CSV) weighting Fourier domain (FD) beamforming for ultrasound plane-wave images was proposed to achieve better image quality with a high frame rate. Firstly, the cosine and sine components of the instantaneous phase are extracted from undelayed RF signals. Secondly, the FD beamformed cosine and sine components are used to establish the CSV. Finally, the FD beamformed amplitude image is weighted by the CSV. The resolution, contrast, and computation complexity were used to assess the performance of the proposed method. The results revealed that FD_CSV could significantly reduce the computational load compared to the conventional DAS_CSV on the equal improvement of image quality. Besides, compared to coherence factor (CF), phase coherence factor (PCF), etc., based on variance calculation, the CSV based on mean resultant vector calculation can effectively preserve the speckle due to the more tolerant to phase errors. The proposed FD_CSV weighting method has successfully conducted high image quality and low computational load.

Real-time 3D imaging with Fourier-domain algorithms and matrix arrays applied to non-destructive testing

Real-time 3D ultrasound imaging with matrix arrays remains a challenge in Non-Destructive Testing (NDT) due to the time-consuming reconstruction algorithms based on delay-and-sum operations. Other algorithms operating in the Fourier domain have lower algorithmic complexities and therefore higher frame rates at the cost of more storage space, which may limit the number of reconstruction points. In this paper, we present an implementation for real-time 3D imaging of the Total Focusing Method (TFM) and the Plane Wave Imaging (PWI), as well as of their Fourier-domain counterparts, referred to as k-TFM and k-PWI. For both types of acquisition, the Fourier-domain algorithms are used to increase frame rates, and they are compared to the time-domain TFM and PWI in terms of image quality, frame rates and memory requirements. In order to greatly reduce their memory requirements, a new implementation of k-TFM and k-PWI is proposed. The four imaging methods are then evaluated by imaging in real time a block of stainless steel containing a 3D network of spherical porosities produced by additive layer manufacturing using a powder bed laser fusion process.

Exploring 3D elastic-wave scattering at interfaces using high-resolution phased-array system

The elastic-wave scattering at interfaces, such as cracks, is essential for nondestructive inspections, and hence, understanding the phenomenon is crucial. However, the elastic-wave scattering at cracks is very complex in three dimensions since microscopic asperities of crack faces can be multiple scattering sources. We propose a method for exploring 3D elastic-wave scattering based on our previously developed high-resolution 3D phased-array system, the piezoelectric and laser ultrasonic system (PLUS). We describe the principle of PLUS, which combines a piezoelectric transmitter and a 2D mechanical scan of a laser Doppler vibrometer, enabling us to resolve a crack into a collection of scattring sources. Subsequently, we show how the 3D elastic-wave scattering in the vicinity of each response can be extracted. Here, we experimentally applied PLUS to a fatigue-crack specimen. We found that diverse 3D elastic-wave scattering occurred in a manner depending on the responses within the fatigue crack. This is significant because access to such information will be useful for optimizing inspection conditions, designing ultrasonic measurement systems, and characterizing cracks. More importantly, the described methodology is very general and can be applied to not only metals but also other materials such as composites, concrete, and rocks, leading to progress in many fields.

The Spectrum-Beamformer for Conventional B-Mode Ultrasound Imaging System: Principle, Validation, and Robustness

Fast and efficient imaging techniques are important for real-time ultrasound imaging. The delay and sum (DAS) beamformer is the most widely-used strategy in focused ultrasound imaging (FUI) modality. However, calculating the time delays and coherently summing the amplitude response in DAS is computationally expensive and generally require a high-performance processor to realize real-time processing. In this study, an efficient spectrum beamformer, namely full-matrix capture (FMC)-stolt, is proposed in FUI system with a linear phased array. The imaging performance of FMC-stolt was validated with the point-scatter simulation and in vitro point and cyst phantoms, and then compared with that of five beamformers, that is, Multiline acquisition (MLA), retrospective transmit beamforming (RTB) in the FUI modality, as well as DAS, Garcia's frequency-wavenumber (f-k), Lu's f-k in the coherent plane wave compounding imaging (CPWCI) modality, under specific conditions. We show that the imaging performance of FMC-stolt is better than MLA-DAS in non-transmit-focal regions, and comparable with RTB-DAS at all imaging depths. FMC-stolt also shows better discontinuity alleviation than MLA and RTB. In addition, FMC-stolt has similar imaging characteristics (e.g., off-axis resolution, computational cost) as the f-k beamformers. The computational complexity and actual computational time indicate that FMC-stolt is comparable to Garcia's f-k, Lu's f-k, and faster than RTB and CPWCI-DAS if the transmitting numbers are close for FUI and CPWCI. The study demonstrates that the proposed FMC-stolt could achieve good reconstruction speed while preserving high-quality images and thus provide a choice for software beamforming for conventional B-mode ultrasound imaging, especially for hand-held devices with limited performance processors.

Short Range Pipe Guided Wave Testing Using SH0 Plane Wave Imaging for Improved Quantification Accuracy

Detection and criticality assessment of defects appearing in inaccessible locations in pipelines pose a great challenge for many industries. Inspection methods which allow for remote defect detection and accurate characterisation are needed. Guided wave testing (GWT) is capable of screening large lengths of pipes from a single device position, however it provides very limited individual feature characterisation. This paper adapts Plane Wave Imaging (PWI) to pipe GWT to improve defect characterization for inspection in nearby locations such as a few metres from the transducers. PWI performance is evaluated using finite element (FE) and experimental studies, and it is compared to other popular synthetic focusing imaging techniques. The study is concerned with part-circumferential part-depth planar cracks. It is shown that PWI achieves superior resolution compared to the common source method (CSM) and comparable resolution to the total focusing method (TFM). The techniques involving plane wave acquisition (PWI and CSM) are found to substantially outperform methods based on full matrix capture (FMC) in terms of signal-to-noise ratio (SNR). Therefore, it is concluded that PWI which achieves good resolution and high SNR is a more attractive choice for pipe GWT, compared to other considered techniques. Subsequently, a novel PWI transduction setup is proposed, and it is shown to suppresses the transmission of unwanted S0 mode, which further improves SNR of PWI.

Ultrasonic Defect Characterization Using the Scattering Matrix: A Performance Comparison Study of Bayesian Inversion and Machine Learning Schemas

Accurate defect characterization is desirable in the ultrasonic nondestructive evaluation as it can provide quantitative information about the defect type and geometry. For defect characterization using ultrasonic arrays, high-resolution images can provide the size and type information if a defect is relatively large. However, the performance of image-based characterization becomes poor for small defects that are comparable to the wavelength. An alternative approach is to extract the far-field scattering coefficient matrix from the array data and use it for characterization. Defect characterization can be performed based on a scattering matrix database that consists of the scattering matrices of idealized defects with varying parameters. In this article, the problem of characterizing small surface-breaking notches is studied using two different approaches. The first approach is based on the introduction of a general coherent noise model, and it performs characterization within the Bayesian framework. The second approach relies on a supervised machine learning (ML) schema based on a scattering matrix database, which is used as the training set to fit the ML model exploited for the characterization task. It is shown that convolutional neural networks (CNNs) can achieve the best characterization accuracy among the considered ML approaches, and they give similar characterization uncertainty to that of the Bayesian approach if a notch is favorably oriented. The performance of both approaches varied for unfavorably oriented notches, and the ML approach tends to give results with higher variance and lower biases.

Optimal Extraction of Ultrasonic Scattering Features in Coarse Grained Materials

Ultrasonic array imaging is used in nondestructive testing for the detection and characterization of defects. The scattering behavior of any feature can be described by a matrix of scattering coefficients, called the scattering matrix. This information is used for characterization, and contrary to image-based analysis, the scattering matrix allows the characterization of defects at the subwavelength scale. However, the defect scattering coefficients are, in practice, contaminated by other nearby scatterers or significant structural noise. In this context, an optimal procedure to extract scattering features from a selected region of interest in a beamformed image is here investigated. This work proposes two main strategies to isolate a target scatterer in order to recover exclusively the time responses of the desired scatterer. In this article, such strategies are implemented in delay-and-sum and frequency-wavenumber forms and optimized to maximize the extraction rate. An experimental case in a polycrystalline material shows that the suggested procedures provide a rich frequency spectrum of the scattering matrix and are readily suited to minimize the effects of surrounding scattering noise. In doing so, the ability to deploy imaging methods that rely on the scattering matrix is enabled.

Visual geometry Group-UNet: Deep learning ultrasonic image reconstruction for curved parts

Detecting small defects in curved parts through classical monostatic pulse-echo ultrasonic imaging is known to be a challenge. Hence, a robot-assisted ultrasonic testing system with the track-scan imaging method is studied to improve the detecting coverage and contrast of ultrasonic images. To further improve the image resolution, we propose a visual geometry group-UNet (VGG-UNet) deep learning network to optimize the ultrasonic images reconstructed by the track-scan imaging method. The VGG-UNet uses VGG to extract advanced information from ultrasonic images and takes advantage of UNet for small dataset segmentation. A comparison of the reconstructed images on the simulation dataset with ground truth reveals that the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) can reach 39 dB and 0.99, respectively. Meanwhile, the trained network is also robust against the noise and environmental factors according to experimental results. The experiments indicate that the PSNR and SSIM can reach 32 dB and 0.99, respectively. The resolution of ultrasonic images reconstructed by track-scan imaging method is increased approximately 10 times. All the results verify that the proposed method can improve the resolution of reconstructed ultrasonic images with high computation efficiency.

Local scattering ultrasound imaging

Ultrasonic imaging is a widely used tool for detection, localisation and characterisation of material inhomogeneities with important applications in many fields. This task is particularly challenging when imaging in a complex medium, where the ultrasonic wave is scattered by the material microstructure, preventing detection and characterisation of weak targets. Fundamentally, the maximum information that can be experimentally obtained from each material region consists of a set of reflected signals for different incident waves. However, these data are not directly accessible from the raw measurements, which represent a superposition of reflections from all scatterers in the medium. Here we show, that a complete set of transmitter–receiver data encodes sufficient information in order to achieve full spatio–temporal separation of transmitter–receiver data, corresponding to different local scattering areas. We show that access to the local scattering data can provide valuable benefits for many applications. More importantly, this technique enables fundamentally new approaches, exploiting the angular distribution of the scattering amplitude and phase of each local scattering region. Here we demonstrate how the local scattering directivity can be used to build the local scattering image, releasing the full potential and richness of the transmit–receive data. As a proof of concept, we demonstrate the detection of small inclusions in various highly scattering materials using numerical and experimental examples. The described principles are very general and can be applied to any research field where the phased array technology is employed.

High-Resolution Ultrasound Imaging Enabled by Random Interference and Joint Image Reconstruction

In ultrasound, wave interference is an undesirable effect that degrades the resolution of the images. We have recently shown that a wavefront of random interference can be used to reconstruct high-resolution ultrasound images. In this study, we further improve the resolution of interference-based ultrasound imaging by proposing a joint image reconstruction scheme. The proposed reconstruction scheme utilizes radio frequency (RF) signals from all elements of the sensor array in a joint optimization problem to directly reconstruct the final high-resolution image. By jointly processing array signals, we significantly improved the resolution of interference-based imaging. We compare the proposed joint reconstruction method with popular beamforming techniques and the previously proposed interference-based compound method. The simulation study suggests that, among the different reconstruction methods, the joint reconstruction method has the lowest mean-squared error (MSE), the best peak signal-to-noise ratio (PSNR), and the best signal-to-noise ratio (SNR). Similarly, the joint reconstruction method has an exceptional structural similarity index (SSIM) of 0.998. Experimental studies showed that the quality of images significantly improved when compared to other image reconstruction methods. Furthermore, we share our simulation codes as an open-source repository in support of reproducible research.

Comparison of Time Domain and Frequency-Wavenumber Domain Ultrasonic Array Imaging Algorithms for Non-Destructive Evaluation

Ultrasonic array imaging algorithms have been widely developed and used for non-destructive evaluation (NDE) in the last two decades. In this paper two widely used time domain algorithms are compared with two emerging frequency domain algorithms in terms of imaging performance and computational speed. The time domain algorithms explored here are the total focusing method (TFM) and plane wave imaging (PWI) and the frequency domain algorithms are the wavenumber algorithm and Lu's frequency-wavenumber domain implementation of PWI. In order to make a fair comparison, each algorithm was first investigated to choose imaging parameters leading to overall good imaging resolution and signal-to-noise-ratio. To reflect the diversity of samples encountered in NDE, the comparison is made using both a low noise material (aluminium) and a high noise material (copper). It is shown that whilst wavenumber and frequency domain PWI imaging algorithms can lead to fast imaging, they require careful selection of imaging parameters.

2D Ultrasonic Antenna System for Imaging in Liquid Sodium

Ultrasonic techniques are developed at CEA (French Alternative Energies and Nuclear Energy Commission) for in-service inspection of sodium-cooled reactors (SFRs). Among them, an ultrasound imaging system made up of two orthogonal antennas and originally based on an underwater imaging system is studied for long-distance vision in the liquid sodium of the reactor's primary circuit. After a description of the imaging principle of this system, some results of a simulation study performed with the software CIVA in order to optimize the antenna parameters are presented. Then, experimental measurements carried out in a water tank illustrate the system capabilities. Finally, the limitations of the imaging performances and the ongoing search of solutions to address them are discussed.