64 results found
Abel R, Behforootan S, Boughton O, et al., 2021, Ultrasound and Bone Disease: A Systematic Review, World Journal of Surgery and Surgical Research
Huang M, Sha G, Huthwaite P, et al., 2021, Longitudinal wave attenuation in polycrystals with elongated grains: 3D numerical and analytical modeling, Journal of the Acoustical Society of America, Vol: 149, Pages: 2377-2394, ISSN: 0001-4966
This work develops a second-order approximation (SOA) model and a three-dimensional (3D) finite element (FE) model to calculate scattering-induced attenuation for elastic wave propagation in polycrystals with elongated grains of arbitrary crystal symmetry. The SOA model accounts for some degree of multiple scattering, whereas the 3D FE model includes all scattering possibilities. The SOA model incorporates the accurate geometric two-point correlation function obtained from the FE material systems to enable comparative studies between the two models. Also, the analytical Rayleigh and stochastic asymptotes are presented to provide explicit insights into propagation behaviors. Quantitative agreement is found between the FE and analytical models for all evaluated cases. In particular, the FE simulations support the SOA model prediction that grain shape does not exert influence on attenuation in the Rayleigh regime and its effect emerges as frequency increases to the stochastic regime showing anisotropy in attenuation. This attenuation anisotropy intensifies with the increase in frequency, but it exhibits a complicated behavior as frequency transits into the geometric regime. Wavefield fluctuations captured from the FE simulations are provided to help observe these complex scattering behaviors. The proportionality of attenuation to elastic scattering factors is also quantitatively evaluated.
Shipway NJ, Huthwaite P, Lowe MJS, et al., 2021, Using ResNets to perform automated defect detection for Fluorescent Penetrant Inspection, Independent Nondestructive Testing and Evaluation (NDT and E) International, Vol: 119, Pages: 102400-102400, ISSN: 0963-8695
Fluorescent Penetrant Inspection (FPI) is a popular Non-Destructive Testing (NDT) method which is used extensively in the aerospace industry. However, the nature of FPI means results are susceptible to the effects of human factors and this can lead to variable results, making automation desirable. Previous work has investigated the use of established machine learning method Random Forest to perform automated defect detection for FPI. Whilst good results were obtained, there was still a significant number of false positives being identified as defective. This paper presents work done to investigate the potential of using deep learning methods to perform automated defect detection.A dataset was obtained from a set of 99 titanium alloy test pieces with cracks induced using thermal fatigue loading. These test pieces were repeatedly processed and using data augmentation a large dataset was obtained. This data was used to train a ResNet34 and ResNet50 architecture as well as a Random Forest. Two significant results were obtained. Firstly, the ResNet50 is able to create a network capable of detecting 95% of defects with a false call rate of 0.07. This result far exceeded that obtained using the Random Forest method despite both methods only having access to a small dataset. This demonstrated the strong capability of deep learning architectures. The second result was that increasing the amount of data obtained from non defective regions significantly increases performance. This result is encouraging as this data, obtained from non-cracked parts, can be quickly and cheaply obtained by reprocessing test pieces.
Zimmermann A, Huthwaite P, Pavlakovic B, 2021, High-resolution thickness maps of corrosion using SH1 guided wave tomography, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 477, ISSN: 1364-5021
Quantifying corrosion damage is vital for the petrochemical industry, and guided wave tomography can provide thickness maps of such regions by transmitting guided waves through these areas and capturing the scattering information using arrays. The dispersive nature of the guided waves enables a reconstruction of wave velocity to be converted into thickness. However, existing approaches have been shown to be limited in in-plane resolution, significantly short of that required to accurately image a defect target of three times the wall thickness (i.e. 3 T) in each in-plane direction. This is largely due to the long wavelengths in the fundamental modes commonly used, being around 4 T for both A0 and S0 at the typical operation points. In this work, the suitability of the first-order shear-horizontal guided wave mode, SH1, has been investigated to improve the resolution limit. The wavelength at the desired operating point is significantly shorter, enabling an improvement in resolution of around 2.4 times. This is first verified by realistic finite-element simulations and then validated by experimental results, confirming the improved resolution limit can now allow defects of maximum extent 3T-by-3T to be reliably detected and sized, i.e. a long-pursued goal of guided wave tomography has been achieved.
Haslinger SG, Lowe MJS, Craster R, et al., 2021, Prediction of reflection amplitudes for ultrasonic inspection of rough planar defects, Insight, Vol: 63, Pages: 28-36, ISSN: 2156-485X
The characteristics of planar defects (no loss of material volume) that arise during industrial plant operation are difficult to predict in detail, yet these can affect the performance of non-destructive testing (NDT) used to manage plant structural integrity. Inspection modelling is increasingly used to design and assess ultrasonic inspections of such plant items. While modelling of smooth planar defects is relatively mature and validated, issues have remained in the treatment of rough planar defect species. The qualification of ultrasonic inspections for such defects is presently very conservative, owing to the uncertainty of the amplitudes of rough surface reflections. Pragmatic solutions include the addition of large sensitivity thresholds and more frequent inspection intervals, which require more plant downtime. In this article, an alternative approach has been developed by the authors to predict the expected surface reflection from a rough defect using a theoretical statistical model. Given only the frequency, angle of incidence and two statistical parameter values used to characterise the defects, the expected reflection amplitude is obtained rapidly for any scattering angle and size of defect, for both compression and shear waves. The method is applicable for inspections of isotropic media that feature surface reflections such as pulse-echo or pitch-catch, rather than for tip signal-dependent techniques such as time-of-flight diffraction. The potential impact for inspection qualification is significant, with the new model predicting increases of up to 20 dB in signal amplitude in comparison with models presently used in industry. All mode conversions are included and rigorous validations using numerical and experimental methods have been performed. The model has been instrumental in obtaining new statistically significant results related to the effect of tilt; the expected pulse-echo backscattered amplitude for very rough planar defects is independent of til
Huang M, Sha G, Huthwaite P, et al., 2020, Elastic wave velocity dispersion in polycrystals with elongated grains: Theoretical and numerical analysis, Journal of the Acoustical Society of America, Vol: 148, Pages: 3645-3662, ISSN: 0001-4966
The phase velocity dispersion of longitudinal waves in polycrystals with elongated grains of arbitrary crystallographic symmetry is studied in all frequency ranges by the theoretical second-order approximation (SOA) and numerical three-dimensional finite element (FE) models. The SOA and FE models are found to be in excellent agreement for three studied polycrystals: cubic Al, Inconel, and a triclinic material system. A simple Born approximation for the velocity, not containing the Cauchy integrals, and the explicit analytical quasi-static velocity limit (Rayleigh asymptote) are derived. As confirmed by the FE simulations, the velocity limit provides an accurate velocity estimate in the low-frequency regime where the phase velocity is nearly constant on frequency; however, it exhibits dependence on the propagation angle. As frequency increases, the phase velocity increases towards the stochastic regime and then, with further frequency increase, behaves differently depending on the propagation direction. It remains nearly constant for the wave propagation in the direction of the smaller ellipsoidal grain radius and decreases in the grain elongation direction. In the Rayleigh and stochastic frequency regimes, the directional velocity change shows proportionalities to the two elastic scattering factors even for the polycrystal with the triclinic grain symmetry.
Huang M, Sha G, Huthwaite P, et al., 2020, Maximizing the accuracy of finite element simulation of elastic wave propagation in polycrystals, Journal of the Acoustical Society of America, Vol: 148, Pages: 1890-1910, ISSN: 0001-4966
Three-dimensional finite element (FE) modelling, with representation of materials at grain scale in realistic sample volumes, is capable of accurately describing elastic wave propagation and scattering within polycrystals. A broader and better future use of this FE method requires several important topics to be fully understood, and this work presents studies addressing this aim. The first topic concerns the determination of effective media parameters, namely, scattering induced attenuation and phase velocity, from measured coherent waves. This work evaluates two determination approaches, through-transmission and fitting, and it is found that these approaches are practically equivalent and can thus be used interchangeably. For the second topic of estimating modelling errors and uncertainties, this work performs thorough analytical and numerical studies to estimate those caused by both FE approximations and statistical considerations. It is demonstrated that the errors and uncertainties can be well suppressed by using a proper combination of modelling parameters. For the last topic of incorporating FE model information into theoretical models, this work presents elaborated investigations and shows that to improve agreement between the FE and theoretical models, the symmetry boundary conditions used in FE models need to be considered in the two-point correlation function, which is required by theoretical models.
Mid-infrared signals in the 2–5 μm wavelength range have been transmitted through samples of polymer pipes, as commonly used in the water supply industry. It is shown that simple through-transmission images can be obtained using a broad spectrum source and a suitable camera. This leads to the possibility of tomography, where images are obtained as the measurement system is rotated with respect to the axis of the pipe. The unusual 3D geometry created by a source of finite size and the imaging plane of a camera, plus the fact that refraction at the pipe wall would cause significant ray bending, meant that the reconstruction of tomographic images had to be considered with some care. A result is shown for a thinning defect on the inner wall of a polymer water pipe, demonstrating that such changes can be reconstructed successfully.
Eckel S, Zscherpel U, Huthwaite P, et al., 2020, Radiographic film system classification and noise characterisation by a camera-based digitisation procedure, Independent Nondestructive Testing and Evaluation (NDT and E) International, Vol: 111, Pages: 1-9, ISSN: 0963-8695
Extracting statistical characteristics from radiographic films is vital for film system classification and contrast sensitivity evaluation and serves as a basis for film noise simulation. A new method for digitising radiographic films in order to extract these characteristics is presented. The method consists of a camera-based setup and image processing procedure to digitise films. Correct optical density values and granularity can be extracted from the digitised images, which are equal to results obtained by standardised measurement procedures. Specific statistical characteristics of film noise are theoretically derived and subsequently verified by the obtained data, including characteristics such as Gaussianity and spatial spectral characteristics of the optical density fluctuations. It is shown that the presented method correctly measures the granularity of film noise and can therefore replace time-consuming microdensitometer measurements traditionally required for film system classifications. Additionally, the inherent unsharpness of film systems was investigated and compared with literature data. This comparison serves as another validation approach of the presented method.
Haslinger SG, Lowe MJS, Huthwaite P, et al., 2020, Elastic shear wave scattering by randomly rough surfaces, Journal of the Mechanics and Physics of Solids, Vol: 137, Pages: 1-20, ISSN: 0022-5096
Characterizing cracks within elastic media forms an important aspect of ultrasonic non-destructive evaluation (NDE) where techniques such as time-of-flight diffraction and pulse-echo are often used with the presumption of scattering from smooth, straight cracks. However, cracks are rarely straight, or smooth, and recent attention has focussed upon rough surface scattering primarily by longitudinal wave excitations.We provide a comprehensive study of scattering by incident shear waves, thus far neglected in models of rough surface scattering despite their practical importance in the detection of surface-breaking defects, using modelling, simulation and supporting experiments. The scattering of incident shear waves introduces challenges, largely absent in the longitudinal case, related to surface wave mode-conversion, the reduced range of validity of the Kirchhoff approximation (KA) as compared with longitudinal incidence, and an increased importance of correlation length.The expected reflection from a rough defect is predicted using a statistical model from which, given the angle of incidence and two statistical parameters, the expected reflection amplitude is obtained instantaneously for any scattering angle and length of defect. If the ratio of correlation length to defect length exceeds a critical value, which we determine, there is an explicit dependence of the scattering results on correlation length, and we modify the modelling to find this dependence. The modelling is cross-correlated against Monte Carlo simulations of many different surface profiles, sharing the same statistical parameter values, using numerical simulation via ray models (KA) and finite element (FE) methods accelerated with a GPU implementation. Additionally we provide experimental validations that demonstrate the accuracy of our predictions.
Jones GA, Huthwaite P, 2020, Fast binary CT using Fourier null space regularization (FNSR), Inverse Problems, Vol: 36, ISSN: 0266-5611
X-ray CT is increasingly being adopted in manufacturing as a non destructive inspection tool. Traditionally, industrial workflows follow a two step procedure of reconstruction followed by segmentation. Such workflows suffer from two main problems: (1) the reconstruction typically requires thousands of projections leading to increased data acquisition times. (2) The application of the segmentation process a posteriori is dependent on the quality of the original reconstruction and often does not preserve data fidelity. We present a fast iterative x-ray CT method which simultaneously reconstructs and segments an image from a limited number of projections called Fourier null space regularization (FNSR). The novelty of the approach is in the explicit updating of the image null space with values derived from a regularized image from the previous iteration, thus compensating for any missing projections and effectively regularizing the reconstruction. The speed of the method is achieved by directly applying the Fourier Slice Theorem where the non-uniform fast Fourier transform (NUFFT) is used to compute the frequency spectrum of the projections at their positions in the image k-space. At each iteration a segmented image is computed which is used to populate the null values of the image k-space effectively steering the reconstruction towards a binary solution. The effectiveness of the method to generate accurate reconstructions is demonstrated and benchmarked against other iterative reconstruction techniques using a series of numerical examples. Finally, FNSR is validated using industrial x-ray CT data where accurate reconstructions were achieved with 18 or more projections, a significant reduction from the 5000 needed by filtered back projection.
Shi F, Huthwaite P, 2019, Waveform-based geometrical inversion of obstacles, Physical Review Applied, Vol: 12, Pages: 1-15, ISSN: 2331-7019
Full-waveform inversion (FWI) can produce previously unobtainable levels of accuracy and is revolutionizing the field of wave imaging. The basic principle is that a numerically produced data set is matched to the measured waveforms, enabling a high-resolution image to be produced since the model being inverted fully captures the physical behavior without approximation. This is achieved by gradually updating the numerical model using optimization algorithms. Currently, most FWI methods aim to recover material properties of a medium containing penetrable scatterers; however, there are many applications that, instead, require the boundary shapes of impenetrable objects to be reconstructed. Conventional velocity-style FWI will be trapped in local minima, with such problems being due to the extremely sharp contrast at the boundary. We propose a FWI procedure to directly recover the geometrical parameters of impenetrable obstacles via shape optimizations. The geometry is reconstructed by iteratively deforming the boundary of the target, following the negative direction of the geometrical boundary gradient. The boundary gradient is calculated from the shape derivatives of mass and stiffness matrices of a finite-element (FE) representation, when distorting the elements attached at the boundary. In addition, multiple-scattering events, which are more likely to occur between impenetrable obstacles, can be utilized automatically to provide substantial information for the inversion. Numerical and experimental results are shown to demonstrate the accuracy of the procedure for an example taken from the field of nondestructive evaluation, giving sizing within fractions of a wavelength for the tested cases; this step change in accuracy could be critical in sizing defects, enabling significantly more reliable decisions to be made about whether it is safe to continue using a component. Mathematical derivations and physical reasons for the success of our approach are illustrated.
Eckel S, Huthwaite P, Zscherpel U, et al., 2019, Realistic film noise generation based on experimental noise spectra, IEEE Transactions on Image Processing, Vol: 29, Pages: 2987-2998, ISSN: 1057-7149
Generating 2D noise with local, space-varying spectral characteristics is vital where random noise fields with spatially heterogeneous statistical proper-ties are observed and need to be simulated. A realistic, non-stationary noise generator relying on experimental data is presented. That generator is desired in areas such as photography and radiography. For example, before performing actual X-ray imaging in practice, output imag-es are simulated to assess and improve setups. For that purpose, realistic film noise modelling is crucial because noise downgrades the detectability of visual signals. The presented film noise synthesiser improves the realism and value of radiographic simulations significantly, allowing more realistic assessments of radiographic test setups. The method respects space-varying spectral characteristics and probability distributions, locally simulating noise with re-alistic granularity and contrast. The benefits of this ap-proach are to respect the correlation between noise and image as well as internal correlation, the fast generation of any number of unique noise samples, the exploitation of real experimental data, and its statistical non-stationarity. The combination of these benefits is not available in exist-ing work. Validation of the new technique was undertaken in the field of industrial radiography. While applied to that field here, the technique is general and can also be utilised in any other field where the generation of 2D noise with local, space-varying statistical properties is necessary.
Haslinger SG, Lowe MJS, Huthwaite P, et al., 2019, Appraising Kirchhoff approximation theory for the scattering of elastic shear waves by randomly rough defects, Journal of Sound and Vibration, Vol: 460, Pages: 1-16, ISSN: 0022-460X
Rapid and accurate methods, based on the Kirchhoff approximation (KA), are developed to evaluate the scattering of shear waves by rough defects and quantify the accuracy of this approximation. Defect roughness has a strong effect on the reflection of ultrasound, and every rough defect has a different surface, so standard methods of assessing the sensitivity of inspection based on smooth defects are necessarily limited. Accurately resolving rough cracks in non-destructive evaluation (NDE) inspections often requires shear waves since they have higher sensitivity to surface roughness than longitudinal waves. KA models are attractive, since they are rapid to deploy, however they are an approximation and it is important to determine the range of validity for the scattering of ultrasonic shear waves; this range is found here. Good agreement between KA and high fidelity finite element simulations is obtained for a range of incident/scattering angles, and the limits of validity for KA are found to be much stricter than for longitudinal wave incidence; as the correlation length of rough surfaces is reduced to the order of the incident shear wavelength, a combination of multiple scattering and surface wave mode conversion leads to KA predictions diverging from those of the true diffuse scattered fields.
Elliott JB, Lowe MJS, Huthwaite P, et al., 2019, Sizing subwavelength defects with ultrasonic imagery: an assessment of super-resolution imaging on simulated rough defects, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol: 66, Pages: 1634-1648, ISSN: 0885-3010
There is a constant drive within the nuclear power industry to improve upon the characterization capabilities of current ultrasonic inspection techniques in order to improve safety and reduce costs. Particular emphasis has been placed on the ability to characterize very small defects which could result in extended component lifespan and help reduce the frequency of in-service inspections. Super-resolution (SR) algorithms, also known as sampling methods, have been shown to demonstrate the capability to resolve scatterers separated by less than the diffraction limit when deployed in representative inspections and therefore could be used to tackle this issue. In this paper, the factorization method (FM) and the Time Reversal Multiple-Signal-Classification (TR-MUSIC) algorithms are applied to the simulated ultrasonic array inspection of small rough embedded planar defects to establish their characterization capabilities. Their performance was compared to the conventional total focusing method (TFM). A full 2-D finite-element (FE) Monte Carlo modeling study was conducted for defects with a range of sizes, orientations, and magnitude of surface roughness. The results presented show that for subwavelength defects, both the FM and TR-MUSIC algorithms were able to size and estimate defect orientation accurately for smooth cases and, for rough defects, up to a roughness of 100 μm. This level of roughness is representative of the thermal fatigue defects encountered in the nuclear power sector. This contrasted with the relatively poor performance of TFM in these cases which consistently oversized these defects and could not be used to estimate the defect orientation, making through-wall sizing with this method impossible.
Egerton JS, Lowe MJS, Huthwaite P, 2019, Automated and antidispersive coherent and incoherent noise reduction of waveforms that contain a reference pulse, NDT & E INTERNATIONAL, Vol: 105, Pages: 35-45, ISSN: 0963-8695
Shipway NJ, Huthwaite P, Lowe MJS, et al., 2019, Performance based modifications of random forest to perform automated defect detection for fluorescent penetrant inspection, Journal of Nondestructive Evaluation, Vol: 38, ISSN: 0195-9298
The established Machine Learning algorithm Random Forest (RF) has previously been shown to be effective at performing automated defect detection for test pieces which have been processed using fluorescent penetrant inspection (FPI). The work presented here investigates three methods (two previously proposed in other fields, one novel method) of modifying the FPI RF based on the individual performance of decision trees within the RF. Evaluating based on the 2 Score, which is the harmonic mean of precision and recall which places a larger weighting on recall, it is possible to reduce the RF in size by up to 50%, improving speed and memory requirements, whilst still gain equivalent results to a full RF. Introducing a performance based weighting or retraining decision trees which fall below a certain performance level however, offers no improvement on results for the increased computation time required to implement.
Shipway N, Barden T, Huthwaite P, et al., 2019, Automated defect detection for Fluorescent Penetrant Inspection using Random Forest, NDT and E International, Vol: 101, Pages: 113-123, ISSN: 0963-8695
Fluorescent Penetrant Inspection (FPI) is the most widely used NDT method in the aerospace industry. Inspection of FPI is currently done visually and difficulties arise distinguishing between penetrant associated with defects and that due to insufficient wash-off or geometrical indications. This, in addition to the nature of the inspection process, means inspection is largely influenced by human factors. The ability to perform automated inspection would provide increased consistency, reliability and productivity.The Random Forest algorithm was used to detect defects in a number of flat titanium plates which had been processed with FPI and photographed to produce digital images. This method has demonstrated the ability to correctly distinguish between defects and other non-relevant indications with accuracy comparable to a human inspector with a very small number of training examples. These results show the potential for the Random Forest algorithm to be used to detect defects in aerospace components, allowing the entire FPI line to become autonomous.
Eckel SF, Huthwaite P, Lowe M, et al., 2018, Establishment and validation of the channelized hotelling model observer for image assessment in industrial radiography, NDT and E International, Vol: 98, Pages: 1-7, ISSN: 0963-8695
A new method for industrial radiography is presented to assess image quality objectively. The assessment is performed by a modelled observer developed to interpret radiographic images in order to rate the detectability of structural defects. For the purpose of qualifying radiographic NDE procedures, computational tools simulate the image, but should additionally automatically assess the associated image quality instead of relying on human interpretation. The Channelized Hotelling Model Observer (CHO) approach, originally developed for medical imaging, is here developed for industrial NDE applications to measure objectively the defect's detectability. A validation study based on a comparison of the model's efficiency of observing circular and elongated flaws shows that the CHO outperforms other detectability models used by industry. Furthermore, the model's reliability was verified by comparing it to psychophysical data.
Zhang C, Huthwaite P, Lowe M, 2018, Eliminating backwall effects in the phased array imaging of near backwall defects, Journal of the Acoustical Society of America, Vol: 144, Pages: 1075-1088, ISSN: 0001-4966
Ultrasonic array imaging is widely used to provide high quality defect detection and characterization. However, the current imaging techniques are poor at detecting and characterizing defects near a surface facing the array, as the signal scattered from the defect and the strong reflection from the planar backwall will overlap in both time and frequency domains, masking the presence of the defect. To address this problem, this paper explores imaging algorithms and relevant methods to eliminate the strong artefacts caused by the backwall reflection. The half-skip total focusing method (HSTFM), the factorization method (FM) and the time domain sampling method (TDSM) are chosen as the imaging algorithms used in this paper. Then, three methods, referred to as full matrix capture (FMC) subtraction, weighting function filtering, and the truncation method, are developed to eliminate or filter the effects caused by the strong backwall reflection. These methods can be applied easily with few tuning parameters or little prior knowledge. The performances of the proposed imaging techniques are validated in both simulation and experiments, and the results show the effectiveness of the developed methods to eliminate the artefacts caused by the backwall reflections when imaging near backwall defects.
Phillips R, Duxbury D, Huthwaite P, et al., 2018, Simulating the ultrasonic scattering from complex surface-breaking defects with a three-dimensional hybrid model, NDT and E International, Vol: 97, Pages: 32-41, ISSN: 0963-8695
Modelling is increasingly relied on for the design and qualification of ultrasonic inspections applied to safety-critical components. Numerical methods enable the simulation of the ultrasonic interaction with realistic defect morphologies; however, the computational requirements often limit their deployment. The hybrid simulation technique, which combines semi-analytical and numerical methods, realises the potential of high fidelity numerical modelling without the limiting computational factors. The inspection of thick section components for near-backwall surface-breaking defects results in large propagation distances, making them a key application of hybrid modelling. This work presents a methodology for efficiently simulating the ultrasonic inspection of complex surface-breaking defects using a hybrid model. The model is initially verified against full numerical simulation; further validation is presented by comparison to an experimental scan over an artificially machined surface-breaking notch. The potential of the new hybrid method is then demonstrated by carrying out a Monte Carlo analysis on the scattered field from surface-breaking defects with randomly rough surfaces and the results are compared to the Kirchhoff approximation.
Shi F, Huthwaite P, 2018, Ultrasonic wave-speed diffraction tomography with undersampled data using virtual transducers, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol: 65, Pages: 1226-1238, ISSN: 0885-3010
Ultrasonic diffraction tomography (DT) offers a way to achieve high-resolution imaging of the wavespeed map, and hence has strong potential applications in medical diagnosis and Nondestructive evaluation (NDE). Ideal images can be obtained with a complete array of sensors surrounding the scatterer, provided that the measurement data are fully sampled in space, obeying the Nyquist criterion. Spatial undersampling causes the image to be distorted and introduce unwanted circular artefacts. In this paper we propose an iteration approach using virtual transducers to achieve high-resolution tomographic imaging with undersampled measurements. At each iteration stage, the extent constraint estimated from the shape of the object of interest is applied on the image space to obtain a regularized image, based on which the ultrasonic measurement data at virtual transducers are calculated using a forward model. The full dataset composed of original and virtual measurements is then used for tomography in the next stage. A final image with sufficiently high resolution is obtained after only a few iterations. The new imaging method yields improvements in the robustness and accuracy of ultrasonic tomography with undersampled data.We present numerical results using complicated wavespeed maps from realistic corrosion profiles. In addition, an experiment using guided ultrasonic waves is performed to further evaluate the imaging method.
Zhang C, Huthwaite P, Lowe M, 2018, The application of the Factorization Method to the subsurface imaging of surfacebreaking cracks, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol: 65, Pages: 497-512, ISSN: 0885-3010
A common location for cracks to appear is at the surface of a component; at the near surface, many nondestructive evaluation techniques are available to inspect for these, but at the far surface this is much more challenging. Ultrasonic imaging is proposed to enable far surface defect detection, location, and characterization. One specific challenge here is the presence of a strong reflection from the backwall, which can often mask the relatively small response from a defect. In this paper, the factorization method (FM) is explored for the application of subsurface imaging of the surface-breaking cracks. In this application, the component has two parallel surfaces, the crack is initiated from the far side and the phased array is attached on the near side. Ideally, the pure scattered field from a defect is needed for the correct estimation of the scatterer through the FM algorithm. However, the presence of the backwall will introduce a strong specular reflection into the measured data which should be removed before applying the FM algorithm. A novel subtraction method was developed to remove the backwall reflection. The performance of the FM algorithm and this subtraction method were tested with the simulated and experimental data. The experimental results showed a good consistency with the simulated results. It is shown that the FM algorithm can generate high-quality images to provide a good detection of the crack and an accurate sizing of the crack length. The subtraction method was able to provide a good backwall reflection removal in the case of small cracks (1-3 wavelengths).
Jones GA, Huthwaite P, 2017, Limited view X-ray tomography for dimensional measurements, NDT and E International, Vol: 93, Pages: 98-109, ISSN: 0963-8695
The growing use of complex and irregularly shaped components for safety-critical applications has increasingly led to the adoption of X-ray CT as an NDE inspection tool. Standard X-ray CT methods require thousands of projections, each regularly distributed evenly through 360∘ to produce an accurate image. The time consuming acquisition of thousands of projections can lead to significant bottlenecks. Recent developments in medical imaging driven by both increasing computational power and the desire to reduce patient X-ray exposure have led to the development of a number of limited view CT methodologies. Thus far these limited view algorithms have been applied to basic synthetic data derived from simple medical phantoms. Here, we use experimental data to rigorously test the capability of limited view algorithms to accurately reconstruct and precisely measure the dimensional features of an additive manufactured sample and a turbine blade. Our findings highlight the importance of prior information in producing accurate reconstructions capable of significantly reducing X-ray projections by at least an order of magnitude. In the turbine blade example a dramatic reduction in projections from 5000 to 24 was observed while still demonstrating the same level of accuracy as standard CT methods. The findings of the study also suggest the importance of sample complexity and the presence of sparsity in the X-ray projections in order to maximise the capabilities of these limited algorithms. With the ever increasing computational power limited view CT algorithms offer a method for reducing data acquisition time and alleviating manufacturing throughput bottlenecks without compromising image accuracy and quality.
Egerton JS, Lowe MJS, Huthwaite P, et al., 2017, A multiband approach for accurate numerical simulation of frequency dependent ultrasonic wave propagation in the time domain, JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, Vol: 142, Pages: 1270-1280, ISSN: 0001-4966
Finite element (FE) simulations are popular for studying propagation and scattering of ultrasonic waves in nondestructive evaluation. For a large number of degrees of freedom, time domain FE simulations are much more efficient than the equivalent frequency domain solution. However, unlike frequency domain simulations, time domain simulations are often poor at representing the speed and the attenuation of waves if the material is strongly damping or highly dispersive. Here, the authors demonstrate efficient and accurate representation of propagated and scattered waves, achieved by combining a set of time domain solutions that are obtained for a set of frequency ranges known as bands, such that, in combination, the authors' multiband solution accurately represents the whole wave spectrum. Consequently, high accuracy is achieved, at minor computational cost, using a modest number of bands. The multiband technique is implemented for ultrasonic wave propagation in highly attenuating polyethylene material, using three frequency bands, and can yield a reduction in empirical acoustic properties fractional error compared with respective time domain simulations, in propagation duration, of a factor of 1.4, and in full-width-half-maximum, of a factor of 10. Last, the accuracy of this approach is further exemplified in a wave scattering simulation.
Egerton JS, Lowe MJS, Huthwaite P, et al., 2017, Ultrasonic attenuation and phase velocity of high-density polyethylene pipe material, JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, Vol: 141, Pages: 1535-1545, ISSN: 0001-4966
Knowledge of acoustic properties is crucial for ultrasonic or sonic imaging and signal detection in nondestructive evaluation (NDE), medical imaging, and seismology. Accurately and reliably obtaining these is particularly challenging for the NDE of high-density polyethylene (HDPE), such as is used in many water or gas pipes, because the properties vary greatly with frequency, temperature, direction and spatial location. Therefore the work reported here was undertaken in order to establish a basis for such a multiparameter description. The approach is general but the study specifically addresses HDPE and includes measured data values. Applicable to any such multiparameter acoustic properties dataset is a devised regression method that uses a neural network algorithm. This algorithm includes constraints to respect the Kramers-Kronig causality relationship between speed and attenuation of waves in a viscoelastic medium. These constrained acoustic properties are fully described in a multidimensional parameter space to vary with frequency, depth, temperature, and direction. The resulting uncertainties in acoustic properties dependence on the above variables are better than 4% and 2%, respectively, for attenuation and phase velocity and therefore can prevent major defect imaging errors.
Huthwaite P, 2017, Ultrasonic finite element simulations on GPUs with Pogo
Haith MI, Huthwaite P, Lowe MJS, 2016, Defect characterisation from limited view pipeline radiography, NDT & E INTERNATIONAL, Vol: 86, Pages: 186-198, ISSN: 0963-8695
This work presents a method of characterising pipeline defects using a small number of radiographs taken at different angles around the pipe. The method relies on knowledge of the setup geometry and use of multiple images, and does not require calibration objects to be included in the setup. It is aimed at use in situations where access is difficult such as in subsea pipeline inspections. Given a set of radiographs, a background subtraction method is used to extract defects in the images. Using a ray tracing algorithm and knowledge of the experimental setup, the range of possible locations of the defect in 3D space is then calculated. Constraints are applied on potential defect shapes and positions to further refine the defect range. The method is tested on simulated and experimental flat bottomed hole defects and simulated corrosion patch defects with lateral and axial sizes ranging from 12.5 to 33.8 mm and thickness between 3 mm and 16 mm. Results demonstrate a good, consistent ability to calculate lateral and axial defect dimensions to within ±3 mm of the true size. Defect thickness calculations are more difficult and as such errors are more significant. In most cases defect thickness is calculated to within 4 mm of the actual value, often closer. Errors in thickness are due to overestimation, meaning the calculation could be used to place a maximum limit on potential defect size rather than as an actual estimate of the thickness. This would still be useful, for example in deciding whether a defect requires further investigation.
Huthwaite P, 2016, Eliminating incident subtraction in diffraction tomography, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 472, Pages: 1-25, ISSN: 1364-5021
Diffraction tomography is a powerful algorithm for producing high-resolution quantitative reconstructions across a wide range of applications. A major drawback of the method is that it operates on the scattered field, which cannot generally be directly measured, but must instead be calculated by subtracting the incident field, i.e. the equivalent field with no scatterer present. Unfortunately, often the incident field is not measurable and hence must be estimated, causing errors. This paper highlights an important, but not widely recognized, result: for particular widely used formulations of the algorithm, the subtraction of the incident field is unnecessary, and the algorithm can actually be applied directly to measured signals. The theory behind this is derived, showing that the incident field will vanish under far-field conditions, and the result is demonstrated in practice. Tests with subsampled arrays show that aliasing artefacts can appear, but can be removed with a filter at the expense of resolution. The incident field also has no effect for a variety of array configurations tested. Finally, the performance in the presence of both correlated and uncorrelated errors is confirmed, in all cases demonstrating that the incident field has a negligible effect on the final reconstruction.
Huthwaite P, 2016, Guided wave tomography with an improved scattering model, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 472, Pages: 1-24, ISSN: 1364-5021
Producing accurate thickness maps of corrosion damage is of great importance for assessing life in the petrochemical industry. Guided wave tomography provides a solution for this, by sending guided waves through the region of interest, then using tomographic imaging techniques to reconstruct the thickness map, importantly eliminating the need to take measurements at all points across the surface. However, to achieve accurate maps, the imaging algorithm must account for the way in which the guided waves interact with corrosion defects, and the complex scattering which occurs. Traditional approaches have exploited the dispersive nature of guided waves: a velocity map is produced from a dataset, then converted to thickness using the dispersion relationship. However, these relationships are derived for plates of constant thickness, which is not the case in the majority of defects, causing significant inaccuracies to exist in the images. This paper develops a more sophisticated inversion solution which accounts for the full-guided wave scattering, enabling more accurate images with resolution better than a wavelength, compared with two wavelengths previously. This is demonstrated with simulated and experimental data. The speed and stability of the algorithm in the presence of random noise and systematic errors is also demonstrated.
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