Crack Sizing Research Articles

A Deep Learning-Based Ultrasonic Diffraction Data Analysis Method for Accurate Automatic Crack Sizing

The purpose of this paper is to automate the interpretation of data during ultrasonic diffraction using a non-destructive testing (NDT) technique to accurately size defects for assisting in decision-making. A convolutional neural network (CNN) architecture was developed to automatically measure the length of the defect. Using the architecture, the population of A-scan signals in the scanning path was classified. The defect region was extracted and its size in the scanning direction was obtained by the connected region solution algorithm based on the classification results. The arrival time of diffraction waves was accurately identified by the intelligent denoising framework proposed, combined with Hilbert transform, and then the height of defects was calculated by corresponding geometric relations. The estimation results demonstrate that the measurement method can be considered as a useful technique for crack sizing in industrial structures, even in the case of complex noise.

Closed cracks characterization in a steel sample applying a pump probe waves ultrasonic method

Abstract Ultrasonic measurements are commonly used for crack sizing in industrial context, but due to potential partial crack closure, the crack depth can be underestimated. It could be of importance regarding the prediction of remaining service life and maintenance scheduling of industrial components. In the literature, nonlinear ultrasonic methods have proven efficient for this issue. Among them, a pump probe waves method is investigated here for possible use in an industrial context. In this paper, an industrial steel component with several partially closed fatigue cracks is studied. First, a three-point bending test associated with digital image correlation is performed with ultrasonic measurements to obtain reliable indications about the cracks closure state. A three-dimensional laser vibrometry experiment shows the possibility to open the crack using a pump wave. The pump probe waves method is conducted using a standard 45° shear wave transducer in echo mode as a probe. The results allow to discuss physical mechanism in play. It is also shown the possibility to detect the closed nature for all of the cracks even if the full opening state is not reached. Moreover, a coherent crack profile is found compared to mechanical test. The results are validated on a notched sample for which the nonlinear response is negligible. Industrial application as well as possible improvement are discussed.

Fastener hole inspection using 2D phased array

Fastener hole cracks, resulting from stress concentration around the hole, are potential sources of failure in mechanical structures. Traditionally, inspection involves manually moving a single ultrasonic probe around the hole or using an eddy current probe to move through the hole. However, single ultrasonic probe inspection is time-consuming and needs skilful operators. Eddy current inspection requires the removal of the fastener in advance and does not allow easy crack sizing and visualization. This paper proposes a novel approach that combines a 2D phased array with a coupling block to enable complete fastener hole inspection from a single array position. A single full matrix capture (FMC) data set is collected, from which 3D volumetric images are formed. To obtain clear images of the geometry and potential defects, half-skip and multi-skip total focusing method imaging algorithms are investigated together with transmitter–receiver pairs selection methods to detect different target features. Experimental results demonstrate that the proposed inspection approach can eliminate dead zone problems and capture all target information from a single inspection position. These methods show great potential in enhancing the efficiency and reliability of fastener hole inspections.

Surface breaking crack sizing method using pulse-echo Rayleigh waves

Surface cracks are common in various industries. Eddy current testing (ECT) is commonly used for crack sizing but necessitates complex calibration standards and a highly trained inspector. Moreover, for large-area inspections, it requires additional scanning arrangements. In recent years the wedge technique-based Rayleigh wave crack sizing method has attracted significant research interest due to its unidirectional excitability. However, Rayleigh wave features generated at crack tips are often weak and masked under noise, and they mostly attenuate before reaching the receiving probe due to the couplant between the wedge-test specimen interface. Consequently, sizing the crack depth is difficult using a pulse-echo setup. This work presents a wedge-free pulse-echo Rayleigh wave method for surface crack sizing using a conventional phased array transducer. Eliminating the wedge removes a couplant layer leading to lower attenuation, enabling the transducer to capture crack tip features. This allows the sizing of surface cracks in pulse-echo using the time-of-flight (ToF) information. Furthermore, leveraging the phased array system, an averaging technique employed to the time trace signals captured by the transducer elements effectively averages out the other wave modes generated at crack geometries by the scattering of Rayleigh waves. This significantly minimizes sizing errors and enhances the signal-to-noise ratio (SNR). The performance of the proposed method is demonstrated through finite element simulations and experiments. Experiments with electric discharged machined (EDM) notches on test specimen surface at various angles and depths mimicking surface-breaking cracks show accurate sizing within a 5% error. The proposed method offers flexibility in performing inspections using a wide frequency range and can be easily applied to different materials using any conventional phased array transducer. This enhances its adaptability for industrial applications in the characterization of surface cracks.

Fast and efficient inversion methods for crack sizing using Bz magnetic signature

AbstractFast estimation is a critical feature of the proposed modeling approach as a “forward” fast solver that has a key role in solving the “inverse” problem involved in crack sizing, especially for real‐time applications. To this end, two different inversion methods have been proposed to estimate the crack depth. The first one uses an interpolation model of the 3D direct model simulation data. The second approach is based on artificial neural networks (ANN). In this article, the rotating uniform eddy current (RUEC) probe is used to detect the normal magnetic component Bz which is defined as the characteristic signal for reconstructing the crack length and depth concurrently. Using the first approach, The Bz characteristic 3D surface is presented, and this can be modeled by a fitted polynomial interpolation equation. Thus, the crack depth can be inverted using this equation referring to the experimental or simulated Bz signal and the crack length. The ANN is outlined to determine the crack depth based on the simulated Bz signature. The move from the first inversion method to the second was flexible and useful, in which the interpolation model is used as a defect signal generator for fast building of a large and efficient database for ANN training. Both of the proposed methods proved the objectivity and accuracy of the inversion results and offered more robust engineering support for automated NDT, reducing production time and increasing productivity.

An alternative Rayleigh wave excitation method using an ultrasonic phased array

Ultrasonic Rayleigh waves have been employed for in-service NDT inspection in a wide range of industries for years. The excitation of Rayleigh waves can be achieved using a variety of methods, with the so-called wedge technique being the most widely used. Recent years have seen considerable research interest in surface crack detection and sizing using Rayleigh waves excited and detected with the wedge technique. However, in this method, Rayleigh waves experience transmission loss at the wedge interfaces. Moreover, the flexibility to generate Rayleigh waves on different waveguides using the same wedge is limited, as the wedge angle depends on the Rayleigh wave wavelength. This work demonstrates a method that provides an alternative Rayleigh wave excitation method. In this, a conventional ultrasonic phased array transducer is used. As there is an appropriate excitation delay between each piezoelectric element of the array transducer, Rayleigh waves can be generated in a wide range of materials using the same phased array transducer. The delay can be estimated based on the elementary pitch of the transducer and the Rayleigh wave velocity of the waveguide. The proposed Rayleigh wave excitation method is demonstrated through both experiments and FE simulations. Furthermore, a finite element model is used to better understand the features of the generated waves and to validate them through their characteristics as Rayleigh wave. A quantitative comparison between the proposed and existing methods is also presented. The directivity and beam divergence of the generated Rayleigh waves are quantified. The results obtained from experiments are in agreement with finite element simulations and demonstrate the possibility of unidirectional and selective excitation of Rayleigh waves through the proposed method. They also highlight the potential for this new excitation method to be used to develop new Rayleigh wave-based inspection methods.

Automatic quantification of concrete cracks via multistage image filtration and trajectory-based local binarization

Ensuring the structural integrity of civil infrastructure and maintaining public safety necessitates accurate and reliable periodic inspection of cracks on concrete surfaces. Image-processing crack detection techniques offer an automated cost-effective alternative for identifying and sizing of cracks. However, the distinctive occurrence of cracks and the presence of environmental noises significantly limit detection capabilities. The method proposed in this study utilizes suitable image enhancement techniques based on the variance in gray pixel intensity in the input image. Moreover, the polynomial curve fit noise detrend technique is used to filter out low frequency noises, including shadows and nonuniform illumination. Symmetry and geometric-based filtration are also sequentially implemented for further crack detection. Furthermore, a trajectory-based local binarization is applied to recover broken crack features due to gray-pixel intensity variations. To achieve accurate and consistent results, the fundamental causes of error in crack sizing are identified and addressed. The proposed algorithm's effectiveness is validated using approximately 80 real images collected from various references. The results demonstrate promising outcomes in actual crack detection and sizing.

An inversion scheme for sizing crack from signals of the motion-induced eddy current testing method based on a new formula of signal gradient of ferromagnetic materials

In this paper, an inversion scheme for the profile reconstruction of a fatigue crack in rails from the motion-induced eddy current testing (MIECT) signals is proposed based on the conjugate gradient (CG) optimization method and the fast MIECT forward simulator developed by authors. To calculate the gradient of MIECT signals with respect to the crack parameters, a simplified analytical gradient formula is deduced, which enables a high efficiency crack reconstruction from MIECT signals for a crack in ferromagnetic material. The validity of the inversion schemes is demonstrated at first by reconstructing cracks with numerical simulated signals for ferromagnetic materials with an oblique elliptic crack model. The good reconstruction results reveal that the new signal grandient formula is efficient for reconstructing crack in ferromagnetic material with the CG algorithm. Finally, sizing of artificial cracks are carried out with use of measured MIECT signals due to cracks in plates of both non-magnetic and ferromagnetic materials. The reconstructed crack parameters are in good agreement with the true values, which experimentally proved the validity and efficiency of the proposed inversion scheme and the new signal gradient formula for MIECT inversion.

Using the Corner Reflection for Depth Evaluation of Surface Breaking Cracks in Concrete by Ultrasound

The corner echo is a well-known effect in ultrasonic testing, which allows detection of surface breaking cracks with predominantly perpendicular orientation to the surface as, for example, corrosion cracks in metal pipes or shafts. This echo is formed by two planes, the surface of the crack and the surface which the crack breaks. It can also be classified as a half-skip method, since a reflection of the pulse occurs on the backwall before the reflection at the defect takes place. In combination with the diffraction from the crack tip, the corner echo also allows crack sizing. As shown in this paper, the corner reflection can be used in civil engineering for nondestructive inspection of concrete. Commercially available low frequency ultrasonic arrays with dry point contact sources generate SH transversal waves with sufficient divergence of the sound field in order to detect corner reflections. Ultrasonic line-scans and area-scans were acquired with a linear array on flat concrete specimens, and the data were reconstructed by the Synthetic aperture focusing technique. If the angles and the area of reconstruction are chosen accordingly, the corner echo reflection can be distinguished from other ultrasonic information. The corner echo can thus be used as a method for deciding whether a crack is a partial-depth crack or a full-depth crack and thus for obtaining a statement about crack depth. This paper presents corresponding experimental results obtained on concrete specimens with artificial test defects and cracks induced under controlled conditions.

Enhanced real-time crack monitoring and updating in welded structural components with limited measurement data

This paper presents an enhanced neural network-bootstrap particle filtering algorithm to construct the complex relationship between the normalized strain relaxation indicators and the crack front profiles based on numerical simulation and experimental validation. The metamodel of normalized strain relaxation indicators and the crack front profile in welded plate joints under bending cyclic loadings is built based on the optimal regression neural network and finite element analysis. To overcome the uncertainties caused by the limited strain measurement, crack measurement, and different non-destructive techniques, this study further proposes new crack-related weight functions and combines a bootstrap particle filtering approach with an interpolation method to finely tune the metamodel and the crack prediction algorithm. As validated by the experimental results, the intelligent crack sizing approach demonstrates a potential solution for crack size monitoring through affordable strain gauges in the broad framework of digitally twinning the next-generation infrastructure.

Reconfigurable Laser-Stimulated Lock-In Thermography for Surface Micro-Crack Detection.

Surface crack detection and sizing is essential for the manufacturing and maintenance of engines, run parts, and other metal elements of aircrafts. Among various non-destructive detection methods, the fully non-contact and non-intrusive technique based on laser-stimulated lock-in thermography (LLT) has recently attracted a lot of attention from the aerospace industry. We propose and demonstrate a system of reconfigurable LLT for three-dimensional surface crack detection in metal alloys. For large area inspection, the multi-spot LLT can speed up the inspection time by a factor of the number of spots. The minimum resolved size of micro-holes is ~50 µm in diameter limited by the magnification of the camera lens. We also study the crack length ranging from 0.8 to 3.4 mm by varying the modulation frequency of LLT. An empirical parameter related to the thermal diffusion length is found to show the linear dependence with the crack length. With the proper calibration, this parameter can be used to predict the sizing of the surface fatigue cracks. Reconfigurable LLT allows us to quickly locate the crack position and accurately measure its dimensions. This method is also applicable to the non-destructive detection of surface or sub-surface defect in other materials used in various industries.

Crack Growth Monitoring with Structure-Bonded Thin and Flexible Coils.

Structural health monitoring with thin and flexible eddy-current coils is proposed for in situ detection and monitoring of fatigue cracks in metallic aircraft structures, providing a promising means of crack sizing. This approach is seen as an efficient replacement to periodic inspections, as it brings economic and safety benefits. As such, printed-circuit-board eddy-current coils are viable for in situ crack monitoring for multi-layer, electrically conductive structures. They are minimally invasive and could be attached to or embedded into the evaluated structure. This work focuses on the monitoring of fatigue crack growth from a fastener hole with structure-bonded, thin, and flexible spiral coils. Numerical simulations were used for optimization of the driving frequency and selection of crack-sensitive coil parameters. The article also demonstrates the fatigue crack detection capabilities using spiral coils attached to a 7075-T6 aluminum coupon.

Low-Velocity Impact, Free-Fall Drop Test of Prototype, and Failure Analysis of Hybrid Palm / Kenaf Reinforced MWCNT Phenolic Composites

ABSTRACT The research’s aim is to investigate the energy absorption, free-fall drop analysis, and failure analysis of Palm (P)/kenaf (K) fiber-reinforced MWCNT-phenolic composites. 3P:7K reinforced MWCNT–phenolic composites were made using manual mixing and hot pressing at 150°C with a pressure of 10 tonnes. Energy absorption was investigated using a drop weight impact tester. Free-fall drop test was performed to analyze the performance of the aircraft tray table prototype. Non-destructive testing was carried out to investigate the damage mechanism. The results demonstrate that as the impact energy increased from 1.50 J to 3.0 J, the crack length increased. There is a difference of 3% to 15% in the crack sizing between dye penetration and Digital Detector Array (DDA), indicating that DDA is more accurate. In the free-fall drop test, small cracks were detected in the dye penetration method on the prototype. The DDA approach, however, did not reveal any defects. The agglomerations were observed through DDA and Computed tomography. In this study, the hybrid CR/kenaf reinforced MWCNT modified phenolic composites exhibit superior performance that can act as an efficient and eco-friendly material for aircraft tray table application by preserving natural resources.

An ultrasonic wave‐based framework for imaging internal cracks in concrete

Nondestructive detection and sizing of internal cracks initiated in reinforced concrete have been critical problems. Geometric characterization of internal cracks and delaminations contributes to predicting their propagation path and failure pattern followed by structural prognostics. There have been limited studies on quantitative detection and characterization of vertical cracks in concrete using wave-based NDE techniques. This study focuses on solving the problem of imaging deep internal crack planes in the concrete medium by leveraging the ultrasonic shear horizontal (SH) waves from a transducer array. Post-processing the array full matrix capture (FMC) data with both total focusing method (TFM) and plane wave imaging (PWI) reveals their efficiency in mapping planar defects inclined between 0° and 60°. However, their performance on vertical/near-vertical defects is found to be inferior with imaging limited to the tip of the defect planes. Further, half-skip modes of wave dispersion have been adopted in addition to the directly scattered pulses for imaging the vertical and near-vertical cracks. We propose an imaging framework based on the outcomes of our investigation on the best suitable methodology to detect and map planar defects like cracks inclined in the range of 0–90°. Statistical quantification of defect inclinations from the reconstructed images is compared to the ground-truth orientations, and they are found to be 94%–99% accurate. Besides accuracy, the computational efficiency of the proposed techniques makes them desirable and reliable for quick on-site inspections on built infrastructure.

Detection and Separation of Close Flaws in Coarse-Grained Materials Using Ultrasonic Image Deconvolution

Ultrasonic inspection of coarse-grained steels is a common challenge in various industrial fields. This task is often difficult because of acoustic scattering that creates structural noise in the ultrasonic signals and images. Therefore, inspections usually use low-frequency probes, which achieve poor resolution with standard delay-and-sum (DAS) imaging techniques, such as the well-known total focusing method (TFM). The purpose of this paper is to evaluate the performance of a super-resolution ultrasonic imaging technique presented by Laroche et al. (IEEE Trans Comput Imaging 7:935–947, 2021) for the inspection of industrial coarse-grained materials. An image deconvolution problem (with spatially varying blur) is formulated, relying on a forward model that links the TFM image to the acoustic reflectivity map. The experiments consider an austenitic-ferritic stainless steel sample insonified using array probes at 3 MHz and 5 MHz placed in contact. The goal is to resolve two close reflectors corresponding to side-drilled holes (SDH) with diameter 0.4 mm spaced by 0.4 mm edge-to-edge and positioned at different depths (10, 20, 30, 40 mm). This configuration corresponds to a critical case where the distance between the two reflectors is much lower than the Rayleigh distance, that is the resolution limit of a DAS imaging system. These are typical cases where DAS images obtained from low-frequency inspections critically lack resolution, but where higher frequency probes cannot be used in practice, because a too week signal-to-noise ratio would affect the detection capability. As predicted by the Rayleigh criterion, TFM is not able to separate the reflectors. The proposed image reconstruction method successfully resolves the majority of the reflectors with a rather accurate distance estimation. In the context of coarse-grained structure inspection, subwavelength reflectors distant from each other by two times less than the resolution limit given by the Rayleigh criterion have been successfully detected and separated. This approach hence enables the use of low-frequency probes, in order to improve the signal-to-noise ratio, while keeping high resolution capability which can be particularly interesting for industrial applications. In particular, the proposed approach shows promising results for the sizing of a real crack in an industrial sample.

3D ultrasonic imaging of surface-breaking cracks using a linear array

Ultrasonic linear arrays have great potential to generate high-quality three-dimensional (3D) images by scanning the array. However, the generated images suffer from low resolution in the elevation plane, limiting the image quality for a reliable 3D Non-Destructive Testing (NDT) inspection. Although several ultrasonic imaging methods have been implemented to inspect different types of defects, there has been limited research to characterise surface-breaking cracks (SBCs) in 3D quantitatively. To improve the characterisation of surface-breaking cracks (SBCs), a 3D hybrid imaging method is proposed by combining the Half Skip Total Focusing Method (HSTFM) and the Synthetic Aperture Focusing Technique (SAFT) using a linear array. This paper proposed the implementation of an array with a reduced element length for full matrix capture (FMC) data acquisition. In conjunction with the hybrid imaging method, a reduced element array enables the utilisation of the information from a broad ultrasonic beam in the elevation direction to achieve improved image resolution. The imaging capability is assessed via a point spread function (PSF) as well as numerical simulations. From the PSF measurements, the image resolution is shown to improve with the smaller element length of the array, which is attributable to the combination of wide beamwidth and hybrid imaging method. Thereafter, experimental validation was performed with arrays of different elevation lengths, where an excellent match with the numerical results was observed. Furthermore, the crack sizing was performed using a 6-dB-drop rule, which assisted in accurately predicting the shape and size of the SBCs and is shown to measure the depth of SBCs with greater confidence. It is shown that a reduced array elevation with the hybrid imaging method and sizing method yields improved image resolution contrary to conventional linear arrays. This approach can offer a significant improvement in manifesting complete comprehension of the spatial defect relationship, enabling NDT engineers to analyse the inspection results quantitatively in 3D for progressive reliability.

Uncertainty Quantification for Deep Learning in Ultrasonic Crack Characterization.

Deep learning for nondestructive evaluation (NDE) has received a lot of attention in recent years for its potential ability to provide human level data analysis. However, little research into quantifying the uncertainty of its predictions has been done. Uncertainty quantification (UQ) is essential for qualifying NDE inspections and building trust in their predictions. Therefore, this article aims to demonstrate how UQ can best be achieved for deep learning in the context of crack sizing for inline pipe inspection. A convolutional neural network architecture is used to size surface breaking defects from plane wave imaging (PWI) images with two modern UQ methods: deep ensembles and Monte Carlo dropout. The network is trained using PWI images of surface breaking defects simulated with a hybrid finite element / ray-based model. Successful UQ is judged by calibration and anomaly detection, which refer to whether in-domain model error is proportional to uncertainty and if out of training domain data is assigned high uncertainty. Calibration is tested using simulated and experimental images of surface breaking cracks, while anomaly detection is tested using experimental side-drilled holes and simulated embedded cracks. Monte Carlo dropout demonstrates poor uncertainty quantification with little separation between in and out-of-distribution data and a weak linear fit ( R=0.84 ) between experimental root-mean-square-error and uncertainty. Deep ensembles improve upon Monte Carlo dropout in both calibration ( R=0.95 ) and anomaly detection. Adding spectral normalization and residual connections to deep ensembles slightly improves calibration ( R=0.98 ) and significantly improves the reliability of assigning high uncertainty to out-of-distribution samples.

A method to compensate for the lift off effect of ACFM in crack estimation of nonferromagnetic metals

Alternating current field measurement (ACFM) is one of the most important techniques for detecting metal cracks. During measurement, however, the changes in lift-off distance caused by coating corrosion and irregularity of the surface greatly affect the accuracy of crack sizing. To overcome this drawback, an advanced algorithm is proposed in this paper to compensate for the lift-off effect. Benefitting from this method, the dimensions of cracks can be inversed directly without considering the lift-off distance. More importantly, the algorithm has been verified efficiently as estimating the cracks of an aluminum workpiece. The results show that the sizing errors based on this algorithm can be limited to 10%.

Analysis on asymmetrical RCF cracks characterisation using an ACFM sensor and the influence of the rail head profile

Rolling contact fatigue (RCF) cracks are one of the typical surface-breaking defects that impairs the rail service life. RCF cracks propagation can deviate from regular semi-ellipse shapes, turning into asymmetrical profiles. RCF crack measurements using the alternating current field measurement (ACFM) method are unable to accurately characterise asymmetrical cracks, as the sizing algorithm is developed based on regular crack shapes. In this paper, the development of modelling capability to consider asymmetrical RCF cracks and the influence of asymmetrical shapes on ACFM signals are presented. A novel grid scan method using ACFM probe sensor for characterizing asymmetrical crack shapes is proposed. The influences of rail head profile on crack sizing are studied and result shows that it gives maximum 2 mm underestimation in crack depth if the worn rail head profile is not considered in ACFM sizing algorithm.

Enhancement of crack reconstruction through inversion of eddy current testing signals with a new crack model and a deterministic optimization method

This paper proposes a new crack model to parameterize profile of a natural crack in order to improve the inversion precision of crack profile with eddy current testing (ECT) signals. In this novel crack model, the edge profile of a planar crack is parametrized with six feature parameters of three curves, i.e. two quarter-elliptic curves and a straight line. Compared with the conventional rectangular and semi-elliptical crack model, the new model gives better profile fitting of actual cracks such as a fatigue crack or a stress corrosion crack. In addition, the reconstruction procedure with the new crack model is more stable than using the arbitrary-shaped crack model outlined by a piecewise line as the unknown parameters to be reconstructed is significantly reduced. To apply the new crack model for crack inversion with the conventional conjugate gradient method, the formulae for calculating the gradient vector regarding to the feature parameters of the new crack model are deduced. To investigate the performance of the new model for crack sizing, cracks of different sizes and complex shapes were reconstructed using the new crack model and the fast forward ECT signal simulator using unflawed field database and the multimedia finite element scheme. Meanwhile, inverse analyses for sizing cracks of complicated shapes were also carried out based on ECT signals containing random noise to clarify the robustness of the new inversion scheme. The numerical results show that reconstructed crack parameters are identical with the true ones in acceptable accuracy, which proved the validity and efficiency of the new method.