Flaw Images Research Articles

Near- and remote-field pulsed eddy current integrated testing for enhancement in imaging of buried flaws in layered conductive structures

ABSTRACT In a bid to simultaneously exploit the advantages of Pulsed Eddy Current testing (PEC) and Pulsed Remote-field Eddy Current Testing (PRFEC) for evaluation of buried defects in layered conductors, in this paper the Near- and Remote-field Pulsed Eddy Current integrated testing (NRPEC) alongside an axi-symmetric probe has been proposed. Simulations are conducted to reveal the field characteristics underlying the proposed method and analyse the signal response to hidden flaws. In parallel, an NRPEC system has been built up. Based on the images of near-field and remote-field signal features, a fusion algorithm is proposed to fuse the signal features of near-field and remote-field signals for defect testing with the enhanced signal-to-noise ratio. Results from simulations and experiments indicate that based on the fused signal feature, high-accuracy imaging of hidden defects in a double-layer conductor can be achieved via NRPEC with the improved signal-to-noise ratio.

Image Generation from Text

Abstract: This work diverts from the usual by using Generative Adversarial Networks (GANs) to intentionally create flawed yet captivating images. We introduce a controlled chaos system, where a stalling generator network and a disoriented discriminator network co-exist. This strange training method encourages the development of peculiar irregularities within semi-realistic images. We welcome the unpredictability that arises from this chaos, purposely avoiding issues like mode collapse. Moreover, the project delves into a new evaluation paradigm for evaluating these deliberately flawed images. We go beyond typical metrics, exploring the use of faulty metrics and questionable visual inspection techniques. In addition, we investigate the impact of clumsy dataset selection, potentially employing unconventional or tampered datasets to train the GAN for specific types of errors. This work explores the potential of GANs for jumbled up art creation, data manipulation, and image confusion, opening a new frontier in GAN applications. While potentially causing confusion in the field, this research also reveals the unimaginable artistic and data exploration capabilities of GANs.

Automated ultrasonic testing for near-surface flaws in CFRP

ABSTRACT In ultrasonic testing of Carbon Fiber Reinforced Polymers (CFRP), signals of near-surface flaws are often submerged in interface signals, resulting in blind spots for defect detection. To address this issue, this paper presents an autocorrelation imaging algorithm that combines Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) with l 0 -norm sparse representation. Firstly, the ultrasonic signal can be modelled as a convolution process. By using MOMEDA, the sequence of reflected pulses in the ultrasonic signal is obtained. Then, the l 0 -norm sparse representation is utilised to enhance the temporal resolution of the sequence, successfully separating near-surface defect signals from interface signals. Finally, the processed data is input into the autocorrelation algorithm, achieving automated imaging of near-surface flaws. Simulation results demonstrate the efficacy of the algorithm in separating overlapping signals. Finally, experimental validation was conducted on flaws at three different depths. The algorithm presented in this paper is capable of identifying all near-surface flaws, with a defect size error rate consistently below 5%.

Rail Flaw Imaging Prototype Based on Improved Ultrasonic Synthetic Aperture Focus Method

This paper presents an experimental prototype developed for rail flaw imaging. This capability can help obtain quantitative information on detected flaws during manual flaw verification. Ultrasonic synthetic aperture focus (SAF) imaging has advantages over phased-array imaging for both speed and accuracy. The prototype developed is hosted in a portable and battery-powered carry-on size case. The probe is a linear ultrasonic array mounted on a wedge and with a position encoder to build 3D point clouds from 2D beamformed images. The prototype includes several advances over the basic SAF technique, including sparse subarray firing that allows fast imaging speeds (e.g., 25 Hz) without sacrificing image accuracy. Validation results are presented from scans performed on rail sections from the FRA rail defect library, which contains natural transverse defects and artificial end-drilled hole defects. The tests showed good accuracy in defect size and shape, as compared to the available ground truth information, for defects located away from the railhead corners. Additional developments are required to properly cover the head corners, and especially in the case of heavily worn rails.

APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR SOLVING PROBLEMS OF ACOUSTIC NONDESTRUCTIVE TESTING (REVIEW)

Nowadays, artificial neural networks are finding more and more applications in various fields of human activity. This paper reviews the current state of research and development in the field of application of artificial neural networks for solving problems in acoustic non-destructive testing. The areas of application of neural networks include processing of inspection data, flaw detection, determination of flaw parameters, and determination of material properties. Test data processing includes increasing the signal-to-noise ratio of results, data compression, restoration and processing of flaw images. Within flaw parameter determination, flaw sizing and flaw type identification tasks have been solved using artificial neural networks. One of the most challenging problems related to the introduction of artificial neural networks in acoustic nondestructive testing is the small amount of inspection data that complicates the training of artificial networks. The ways to solve this problem are data exchange between organizations and standardization of inspection results, data augmentation and application of computer modeling.

Ultrasonic tomography using sparse antenna arrays and frequency domain post-processing

Currently, an important problem for industrial ultrasonic tomography using post-processing of matrix phased arrays signals is the improving restoration speed of results in the form of images of flaws in inspected objects. One of the approaches aimed at solving this issue is the application of sparse matrix antenna arrays. In this paper, we consider the use of the sparse matrix probes operating in a separate mode of signals acquisition together with the post-processing algorithm using the calculations in frequency-domain. Considered algorithm is based on the application of non-uniform fast Fourier transform. The efficiency of the considered approach is verified via in-situ experiments.

Anisotropy Corrected FMC/TFM Based Phased Array Ultrasonic Imaging in an Austenitic Buttering Layer

For the narrow gap dissimilar weld between a ferritic steel and a nickel base superalloy, a nickel base alloy buttering layer is deposited on the ferritic steel side as an intermediate layer. The bonding between the buttering layer and the ferritic steel is required to be inspected from the buttering layer side. The buttering layer exhibits very high elastic anisotropy due to elongated columnar grains with preferred orientations. In this paper, the effect of elastic anisotropy on the phased array ultrasonic imaging of defects in the buttering layer is demonstrated for data acquired in full matrix capture (FMC) mode and reconstructed with the total focusing method (TFM). The anisotropy in the buttering layer leads to distorted flaw images, which limits the lateral resolution and defect detection sensitivity. Angle-dependent ultrasonic velocity measured in through-transmission FMC mode has been used for processing the FMC data to obtain high-resolution TFM images with improved sensitivity. The velocity values used are in line with the grain orientations observed by electron-backscatter diffraction (EBSD) studies. Further, an alternate approach is also proposed to obtain a TFM image with improved resolution using a suitable isotropic velocity. The approach can be implemented in any commercial phased array ultrasonic system having the FMC-TFM feature.

Finite Element Simulation of Ultrasonic Scattering by Rough Flaws with Multi-Scale Distortions.

The roughness of a flaw's surface significantly affects the scattering behavior of ultrasonic waves. It is vital to understand the impact of roughness on flaw echoes, especially when performing ultrasonic nondestructive inspection on safety-critical components. However, the current approach for creating rough flaw models fails to reconstruct complicated cracks with secondary cracks. Here, a multi-scale distortion method is developed to generate a rough flaw by using an optical microscope image of a real flaw. The finite element (FE) is then implemented to simulate the near-surface rough flaws in nickel-based bars, which are detected by an offsetting immersion transducer with mode-converted transverse waves. Numerical results show that the randomness and complexity of flaw echoes from rough flaws are exceptionally high. The gap between the maximum and minimum normalized amplitude values of flaw echoes from a rough crack with secondary cracks can reach 7.125 dB. Meanwhile, the maximum time of flight (TOF) is almost twice as large as the minimum TOF. Therefore, the present method can generate effective rough flaw models in terms of macroscopic rough geometry and microscopic rough surface. Moreover, the impact of the rough flaw surface on the flaw echoes goes beyond amplitude changes and may make flaw location challenging.

Ultrasonic C-scan image restoration method using the Richardson-Lucy algorithm and a flaw measurement model

In ultrasonic imaging, blurred edges have a heavily negative impact on the accuracy of the flaw images. To improve ultrasonic C-scan image quality, this paper proposes a deconvolution-based ultrasonic C-scan image restoration method combining the Richardson-Lucy (RL) algorithm and a flaw measurement model. In order to implement an optimal restoration process, an ultrasonic C-scan imaging model is presented and employed to simulate the C-scan images. By restoring the simulated images, a relationship between the optimal iteration number and the ratio of the flaw size to the sound wavelength is established. Furthermore, the equivalent sizes of the flaws are extracted from a flaw measurement model-based non-destructive approach and are used to calculate the optimal iteration number of the RL deconvolution algorithm. Finally, the experimental ultrasonic C-scan images are restored by using the RL iterative algorithm with the optimal iteration numbers, 1, 2, 6, and 14, respectively. The experimental results show that the flaw sizes, obtained by the 6 dB drop method in the original C-scan images, have errors larger than 26 %. After restoration, the maximum error of the flaw size in the C-scan image is only 10 % and the minimum is 2 %, indicating that the proposed restoration method effectively improves the accuracy of the ultrasonic C-scan imaging.

Empirical mode decomposition based techniques for imaging of shallow delamination in concrete using impact echo

An impact echo (IE) signal comprises different frequency components as a result of interaction between stress waves and targets. Empirical mode decomposition (and its improved techniques), an adaptive and fully data-driven technique have been used to separate different components of an IE signal into what is known as intrinsic mode functions (IMF). The applications of improved versions of EMD and their advantages over other new adaptive decomposition techniques have also been demonstrated. This separation of modes differentiates constituent signals such as surface wave, echo wave, and flexural wave into corresponding IMFs and thus allows reconstruction of a new signal using only desirable components. An image reconstruction strategy for the selection of appropriate IMFs based on correlation coefficient is found to produce an improved image of the delamination or flaws compared to the raw signal images. The IE signal processed with noise-assisted EMD based techniques profoundly increased the accuracy of flaw features over the raw data. This improvement is validated with a quantification approach using amplitude histogram and binary mapping of flaws in B-scan and C-scan respectively. The study demonstrated that the flexural mode of vibration produced due to shallow delamination can be used for accurate imaging of flaws provided a suitable signal processing technique is used. The technique employed in this study can also be extended for imaging of deep delamination which is exhibited by echo waves in IE signals.

A Study on the Scan Plans for Rapid Flaw Detection by Eddy Current Non-Destructive Evaluation

Raster, diagonal-raster, spiral, Lissajous, and billiard type scan plans have been analysed, for the first time, in eddy current testing for detection and imaging of flaws. The performance of these scan plans has been studied by using metrics like rapidness, complete coverage, and step size. Numerical investigations have been carried out to evaluate the performance of the five scan plans for the detection of 1000 randomly located notches in a stainless steel plate. Studies indicate that the billiard scan plan results in 98.5% detection as compared to the other scan plans, and this has been verified experimentally. Results clearly show that the billiard scan plan ensures the rapid detection of flaws in large surfaces of electrically conducting materials by eddy current testing.

Experimental Validation of Ultrasonic Imaging Using Topological Derivative

We investigated an array ultrasonic imaging method using the topological derivative. The topological derivative is formulated based on the sensitivity of the cost functional associated with the inverse scattering problem due to the creation of an infinitesimal rigid inclusion. To calculate the topological derivative, time convolutions of a free field and a supplementary adjoint field are required. In this study, scattered waves from flaws were received with an array transducer, then the supplementary adjoint field using the measured waves was calculated in the framework of the finite integration technique (EFIT). Finally, flaw imaging was performed by plotting the obtained topological derivative in the target region.

Application of Matrix Array Transducer for Non-destructive Photoacoustic Imaging

In general, it is challenging to evaluate subsurface flaws of a target material because of a dead zone of surface echo in nondestructive ultrasonic testing. In this study, photoacoustic (PA) imaging using a matrix array transducer was applied to reconstruct the three-dimensional shape of subsurface flaws in carbon fiber reinforced plastic (CFRP). The matrix array transducer can receive the scattered signal individually and enhance the total intensity by setting a delay for each element. In this study, we selected several focal depths and reconstructed the flaw shape using the synthetic aperture focusing technique. The result showed that adequate delay design was necessary for accurate flaw imaging.

A new high-frequency eddy current technique for detection and imaging of flaws in carbon fibre-reinforced polymer materials

Using a high-frequency (50 kHz-4 MHz) alternating current field measurement (ACFM)-style inspection, non-destructive imaging of carbon fibre-reinforced polymers (CFRPs) was performed for the detection and evaluation of flaws developed during their manufacture or in-service use. This was achieved using quantum well Hall-effect (QWHE) sensors, which have proven suitability for use in different non-destructive testing and evaluation (NDT&E) applications based on their high sensitivity (they require lower strength applied fields and can detect smaller perturbations in the magnetic field), high linearity (high contrast and imaging evaluation capabilities), wide dynamic range (making them less sensitive to offset and lift-off variations), wide frequency operating range (DC to MHz) and compact size (5-70 microns depending on the application). Their advanced III-V semiconductor materials and design enable these characteristics. Their low capacitance allows them to be operated at significantly higher frequencies than coils of comparable sensitivity or size. As such, the inherent advantages of QWHE sensors have been used in conjunction with a high-frequency ACFM-style magnetic imaging inspection technique, which is referred to as quantum well eddy current field measurement (QW-ECFM) in this paper. Here, the fundamentals of this new technique are outlined, as well as the outcomes of such a technique for evaluating CFRP materials, where individual fibre bundles have been resolved in high detail with high contrast. In addition, the ability to detect fibre misalignment has been shown, suggesting technique sensitivity to 3D orientations of fibre for better material qualification and the detection of delamination down to 2 mm in diameter. Therefore, this paper aims to provide an overview of this new QW-ECFM technique and summarise its performance for the detection and evaluation of various CFRP material flaws that are commonly found during manufacture and service.

Optimising sensor pitch for magnetic flux leakage imaging systems

Sensor arrays can significantly increase the speed at which inspections and subsequent imaging of flaws is performed[1]. This work focuses on developing a software approach for optimising the spacing between quantum well Hall-effect (QWHE) magnetic sensors used for magnetic flux leakage (MFL) imaging, where this approach could be adapted for any non-destructive evaluation (NDE) technique in which imaging is obtained. A ground mild steel weld sample containing two surface-breaking flaws prepared by Sonaspection was scanned using an XYZ MFL imaging system developed at the University of Manchester[2,3,13,14]. The scan was taken with an autonomously controlled lift-off height of 0.75 mm, with an x-y measurement step of 100 μm and an applied magnetic field of 30 mT root mean square (RMS) at a frequency of 400 Hz. This data (ie magnetic image) was then processed to simulate different measurement step sizes, to determine any relationship between step size and flaw detectability (flaw signal to weld background response). This work effectively simulates different sensor pitches (separation between sensors) of integrated QWHE sensor arrays from 100 μm to 5 mm, with the goal of determining both the minimum number of sensors required in the array and the optimal spacing to maximise scan speeds and help determine optimum inspection parameters to develop the technology of low-power MFL imaging. This optimisation process could be applied to any NDE imaging system (electromagnetic or other) currently used, with results dependent on the inspection parameters.

Component shape optimisation for enhanced non-destructive testing

Determining an optimal component design is fundamental to many applications including many of those in the aerospace, automotive and civil engineering industries. Previously, the compatibility of the component with future non-destructive testing (NDT) requirements has not been considered at the design stage. As a result, NDT operators are often challenged to reliably inspect components with complex geometries. In this paper, a framework is proposed for the optimisation of a component's shape to maximise the sensitivity and coverage of an interrogating ultrasonic wave, thus enhancing the ability to non-destructively image defects. The design of beam cross-sections are optimised using both a low-dimensional parameterisation with a genetic algorithm, and the level set method which enables more degrees of freedom in the component shape parameterisation. Images of flaws computed using the total focusing method show an 8 dB improvement in the signal to noise ratio for the optimised component as well as a five-fold improvement in the estimate of flaw size. These results show that the NDT-optimised design of components can provide significant improvements in flaw imaging. This in turn assists in extending the lifespan of in-service components and indeed their remanufacturability, which is both environmentally and economically advantageous.

Non-linear Phased Array Imaging of Flaws Using a Dual and Tri Frequency Modulation Technique

Recently, there has been high interest in the capabilities of nonlinear ultrasound techniques for damage/defect detection as these techniques have been shown to be more sensitive than linear ultrasound techniques for certain types of damage. This paper presents a nonlinear ultrasound phased array modulation method based on the principles of frequency and amplitude modulation, for the detection and imaging of material defects/damage. The proposed method requires the use of standard ultrasound phased array systems, which use multiple transmitting and receiving elements. An adjusted dual frequency method and tri-frequency is employed, which focuses on the evaluation of harmonic sidebands. A pump signal at a frequency of f2 is used to initialise a ‘breathing/ringing’ crack scenario after which a second frequency at f1 is used to further excite the crack and improve the probability that harmonic sidebands are generated. The modulation method employs a subtraction method which is used to filter out the fundamental frequencies. The technique adds benefits in ensuring that equipment based nonlinearities produced by single frequency setups are eliminated, ensuring that only defect related nonlinearities are present. A closed fatigue crack was evaluated using multiple linear and nonlinear ultrasound phased array techniques with the suggested method showing clear benefits. Furthermore, it is shown that modulation techniques with more than two driving frequencies could further improve damage detection capabilities of phased array systems.

Elastic least-squares reverse-time migration with density variation for flaw imaging in heterogeneous structures

Ultrasonic techniques are able to accurately detect and characterize flaws in homogeneous structures. Elastic reverse time migration (ERTM) is a powerful tool to reconstruct high-resolution images of flaws. To achieve images with better quality, the solution can be obtained by iteratively finding an image generating the modeled data which can best match the measured data in a least-squares sense, i.e. least-squares migration (LSM). Combing ERTM and LSM, conventional elastic least-squares reverse time migration (ELSRTM) methods are based on the assumption of a constant density, which can lead to inaccurate amplitudes and parameter crosstalk artifacts in the reconstructed images. In this paper, an ultrasonic imaging technique based on the ELSRTM which considers density as well as longitudinal-(L-) and shear-wave (S-wave) velocity variations is explored for imaging flaws in heterogeneous structures. The ELSRTM with density variations can simultaneously reconstruct density and L- and S-wave velocity images, which can provide amplitude-preserving images and mitigate crosstalk artifacts. This method is applied to numerical as well as physical laboratory experiments and the results appear promising for flaw identification in heterogeneous structures.

Flaw Imaging by Ultrasonic Lamb Waves Utilizing Dispersion Compensation

Flaw Imaging by Ultrasonic Lamb Waves Utilizing Dispersion Compensation

Europe Has Never Been Modern: Recasting Historical Narratives of Migration Control

AbstractOur understanding of contemporary international relations rests on flawed images of the past. One of the most problematic dimensions of this history is the idea that the core institutions and practices of modern territorial sovereignty originated in Europe before being gradually extended to other parts of the globe. A key dimension of this Euro-centric historiography is the story that the territorial sovereignty norm was invented in Europe in the seventeenth century, before Europeans honed it into a standard technique of state practice in the twentieth. This paper uses original archival research to critically interrogate the consensus position. The paper demonstrates that the dominant narrative significantly misconstrues the way rulers and governments sought to control migration across the longue durée. European rulers were more collectively seeking to transnationally promote migration at the same time as they individually acquired territorial sovereign control over it. Extra-European states were the first to deploy territorial immigration controls, and non-Europeans shaped the forms of mobility promotion Europeans would adopt. The paper uses these findings to make the case for a new chronology of European migration governance and for a critical institutionalist approach to the way we write the history of the global migration regime.