Showing papers in "Ndt & E International in 2021"

An automatic welding defect location algorithm based on deep learning

Abstract: Welding production has a pivotal role in the modern manufacturing industry. However, welding defects are frequently generated during the complex welding production process which will bring a certain effect to the welding quality. Therefore, the issue of welding defect detection has received considerable critical attention. However, traditional methods, based on handcrafted features or shallow-learning techniques could only detect welding defects under specific detection conditions or priori knowledge. In this paper, to serve the evaluation of the harmfulness of welding defects to different objects, based on the strong feature expression ability of deep learning, an automatic welding defect location method is proposed based on the improved U-net network from digital X-ray images which includes data augmentation and welding defect location. To acquire better location performance, the data augmentation is realized to enlarge the data set of welding defects to serve the network training. On the basis, a defect location method based on the improved U-net network is proposed to realize automatic and high-precision welding defect location. Experiments show that the proposed method could acquire the detection precision up to 88.4 % on the public data set (GDXray Set) which shows a remarkable location performance compared with other related detection methods.

Effect of tensile stress on metal magnetic memory signals during on-line measurement in ferromagnetic steel

Abstract: Metal magnetic memory testing (MMMT) is a promising nondestructive technique for early damage evaluation of ferromagnetic materials due to its high sensitivity to the stress state. An experimental investigation of the effect of axial applied stress on MMMT signals, both the normal component B z and the tangential component B x , under on-line loaded and unloaded measurement condition has been carried out during the whole tensile test in 0.45%C steel. In the elastic deformation stage, B z signal kept rotating counterclockwise while B x signal kept moving upward under on-line measurement both when loaded and unloaded, but the MMMT signals measured unloaded tended to resume the initial state compared those measured loaded. In the plastic deformation stage, B z signal rotated clockwise while B x signal moved downward under on-line loaded measurement with the increase of tensile stress, while the MMMT signals measured unloaded reversed compared those measured loaded. The results of the present work indicate that MMMT is a feasible solution for stress state on-line monitoring of ferromagnetic components.

Rapid detection of cracks in the rail foot by ultrasonic B-scan imaging using a shear horizontal guided wave electromagnetic acoustic transducer

Abstract: Transverse cracks in the rail foot are responsible for the breaking of the rail. The existing non-destructive testing technology for high-speed railway track is difficult to perform in-situ and rapid detection for the rail foot, which poses a hidden danger to driving safety. In this study, a new method is proposed for the in-situ and rapid detection of cracks in the rail foot by ultrasonic B-scan imaging. A finite element method (FEM) based on the Bloch–Floquet boundary and domain constraint were employed to calculate the dispersion curves of shear horizontal (SH)-like guided waves propagating in the rail foot. SH guided waves mainly vibrate with in-plane displacement, and they are less affected by the rail components such as elastic clips and pads. Based on the calculated dispersion curves, an SH-guided wave electromagnetic acoustic transducer (EMAT) with a center frequency of 0.154 MHz was developed, and ultrasonic B-scan imaging was performed to detect straight cracks in the rail foot. Besides, the synchrosqueezed wavelet transform (SWT) method was proposed to remove noises and higher-order guided wave modes from the original ultrasonically detected signals. Results show that FEM with the Bloch–Floquet boundary and domain constraint can be used to solve the dispersion curves of the SH-like guided waves of the rail foot accurately and easily. The application of SWT can increase the lift-off of the EMAT, eliminate the noise, remove the higher-order SH-like guided wave modes, improve the detection efficiency, and enhance the quality of ultrasonic B-scan images. After the SWT processing, the signal-to-noise ratio (SNR) of the ultrasonic signal is increased by at least 5.98 dB. When the lift-off of the EMAT is 4 mm and without synchronous averaging, the on-line and rapid ultrasonic B-scan imaging of the rail foot using guided wave EMAT can still achieve a reasonable SNR.

Defect sizing in guided wave imaging structural health monitoring using convolutional neural networks

Abstract: This paper proposes an automatic defect localization and sizing procedure for Structural Health Monitoring based on guided waves imaging. The procedure is applied to an aluminum plate equipped with active piezoelectric sensors. The defect localization and sizing strategy is obtained through to the use of a convolutional neural network trained exclusively on numerical simulations of guided wave signals and post-processed by the delay and sum imaging algorithm. The paper shows the effectiveness of the proposed approach to invert both synthetic and experimental data.

Experimental investigation of the surface corrosion damage in plates based on nonlinear Lamb wave methods

Abstract: This paper experimentally investigates the early stage damage caused by the surface corrosion in thin plates based on two nonlinear Lamb wave methods, which are the low-frequency S0 mode Lamb wave method and one-way S0-A0 Lamb mixing wave method. The experimental results show that the significant second/third harmonics and the resonant waves from these methods can be caused by the surface corrosion damage. Meanwhile, it is found that the normalized acoustic nonlinearity parameters in these methods increase monotonically with the number of corrosion times before the generation of the distinct cavities. Moreover, the position and the length of the surface corrosion region can be characterized by the resonant waves from one-way S0-A0 Lamb mixing wave method. This study reveals that the low-frequency S0 mode Lamb wave method and one-way S0-A0 Lamb mixing wave method are feasible to evaluate early stage damage caused by the surface corrosion.

Damage Quantification in an Aluminium-CFRP Composite Structure using Guided Wave Wavenumber Mapping: Comparison of Instantaneous and Local Wavenumber Analyses

Abstract: Composite-overwrapped pressure vessels (COPV) are increasingly used in the transportation industry due to their high strength to mass ratio. Throughout the years, various designs were developed and found their applications. Currently, there are five designs, which can be subdivided into two main categories - with a load-sharing metal liner and with a non-load-sharing plastic liner. The main damage mechanism defining the lifetime of the first type is fatigue of the metal liner, whereas for the second type it is fatigue of the composite overwrap. Nevertheless, one damage type which may drastically reduce the lifetime of COPV is impact-induced damage. Therefore, this barely visible damage needs to be assessed in a non-destructive way to decide whether the pressure vessel can be further used or has to be put out of service. One of the possible methods is based on ultrasonic waves. In this contribution, both conventional ultrasonic testing (UT) by high-frequency bulk waves and wavenumber mapping by low frequency guided waves are used to evaluate impact damage. Wavenumber mapping techniques are first benchmarked on a simulated aluminium panel then applied to experimental measurements acquired on a delaminated aluminium-CFRP composite plate which corresponds to a structure of COPV with a load-sharing metal liner. The analysis of experimental data obtained from measurements of guided waves propagating in an aluminium-CFRP composite plate with impact-induced damage is performed. All approaches show similar performance in terms of quantification of damage size and depths while being applied to numerical data. The approaches used on the experimental data deliver an accurate estimate of the in-plane size of the large delamination at the aluminium-CFRP interface but only a rough estimate of its depth. Moreover, none of the wavenumber mapping techniques used in the study can quantify every delamination between CFRP plies caused by the impact, which is the case for conventional UT. This may be solved by using higher frequencies (shorter wavelengths) or more advanced signal processing techniques. All in all, it can be concluded that imaging of complex impact damage in fibre-reinforced composites based on wavenumber mapping is not straightforward and stays a challenging task.

Quantitative method for detecting internal and surface defects in wire rope

Abstract: The detection of internal and external defects in steel wire rope is a very important task. Current nondestructive testing methods cannot distinguish between internal and surface defects, and cannot determine the quantitative characteristics of internal defects. This paper first analyzes the advantages and disadvantages of induction coil magnetic flux detection and Hall sensor-based magnetic flux leakage detection. The problem of simultaneous detection using these two methods is then solved, and a new quantitative detection method is proposed for internal and surface defects in wire rope. Finally, a calculation method that uses a two-step training algorithm to establish two sets of neural networks is proposed. Results from simulations and experiments verify that the proposed method can accurately distinguish between internal and surface defects in wire rope, and can also quantitatively detect the width, cross-sectional loss rate, and depth of the defects.

Lift-off invariant inductance of steels in multi-frequency eddy-current testing

Abstract: Eddy current testing can be used to interrogate steels but it is hampered by the lift-off distance of the sensor. Previously, the lift-off point of intersection (LOI) feature has been found for the pulsed eddy current (PEC) testing. In this paper, a lift-off invariant inductance (LII) feature is proposed for the multi-frequency eddy current (MEC) testing, which merely targets the ferromagnetic steels. That is, at a certain working frequency, the measured inductance signal is found nearly immune to the lift-off distance of the sensor. Such working frequency and inductance are termed as the lift-off invariant frequency (LIF) and LII. Through simulations and experimental measurements of different steels under the multi-frequency manner, the LII has been verified to be merely related to the sensor parameters and independent of different steels. By referring to the LIF of the test piece and using an iterative inverse solver, one of the steel properties (either the electrical conductivity or magnetic permeability) can be reconstructed with a high accuracy.

Automated defect detection for ultrasonic inspection of CFRP aircraft components

Abstract: An automated task sequence based on the commercial software Ultis® combined with new pre- and post-processing tools was developed to achieve a fully automated analysis of ultrasonic data obtained from large and complex CFRP components. The resulting a90/95 on reference panels containing a variety of artificial defects was 6.8 mm. The new tools include a C-scan projection optimizer that minimizes defects distortion during 3D to 2D transition, an efficient segmentation method to address challenging features (co-cured stringers, ply drop-offs, multiple thickness variations), and a novel defect detection algorithm capable of automatically extracting indications from a collection of A-scans. Results suggest that the method meets the detection requirements while significantly reducing the analysis time.

Debonding detection in rebar-reinforced concrete structures using second harmonic generation of longitudinal guided wave

Abstract: Nonlinear features of ultrasonic guided waves (GWs) is studied for debonding detection and location estimation in rebar reinforced concrete structure. The study shows that the presence of debonding between steel rebar and concrete surface produces breathing phenomenon causing contact acoustic nonlinearity (CAN), which generates second harmonics. Time-frequency analysis is used to estimate the location of debonding in this study. At a particular frequency, embedded rebar has much greater number of wave modes in bare rebar. To avoid unnecessary complexity, only longitudinal GW modes for bare and embedded rebar are excited and received to detect and locate debonding. To precisely determine the wave mode at excited frequency and frequency of second harmonics, frequency-wavenumber analysis is performed using 2D-Fast Fourier Transform of time-space data. Three-dimensional explicit finite element simulations are performed for various case studies and the model is validated by experimentally measured data. The results of this study show that the proposed method is practically viable and beneficial for debonding detection and location estimation in reinforced concrete structures.

Comparative study of ultrasonic techniques for reconstructing the multilayer structure of composites

Abstract: The multilayer structure of fiber-reinforced polymers may be extracted by ultrasonic pulse-echo inspection. Depending on the employed ultrasonic frequency and subsequent processing methodology, different depth resolution and dynamic depth range can be achieved. This study compares the performance of different ultrasonic pulse-echo approaches for extracting the ply-by-ply structure of multilayered composites. The following methodologies are studied: Method 1: 50 MHz, 15 MHz, and 5 MHz ultrasound with low-pass filtering using analysis of the instantaneous amplitude, Method 2: 15 MHz ultrasound with Wiener deconvolution (and autoregressive spectral extrapolation) using analysis of the instantaneous amplitude, and Method 3: 5 MHz ultrasound with low-pass or log-Gabor filtering using analysis of the instantaneous phase. In the simulation study, the performance of the various techniques is investigated on synthetic data representative for a 24-ply carbon fiber reinforced polymer. The robustness of the techniques is evaluated for different signal-to-noise ratios. The various techniques are further investigated on experimental data of a 24-ply cross-ply carbon fiber reinforced polymer. The ply-by-ply structure is extracted and presented in the form of both B-scan and C-scan images. The thickness of each ply is estimated for quantitative analysis. The obtained results indicate that the 5 MHz ultrasound coupled to analytic-signal analysis with log-Gabor filter shows the best performance for reconstructing the multilayer structure of the studied composites.

Frequency component mixing of pulsed or multi-frequency eddy current testing for nonferromagnetic plate thickness measurement using a multi-gene genetic programming algorithm

Abstract: For the efficient use of frequency components, a frequency mixed feature for pulsed eddy current testing (PECT) or multi-frequency eddy current testing (MultiECT) was proposed for nonferromagnetic plate thickness measurement. An evolutionary algorithm multigene genetic programming was employed to mix the frequency components using the best linearity as a target. Time domain and frequency domain finite element simulations of PECT and MultiECT were conducted. The simulation results revealed that, in terms of thickness measurement, a mixed feature comprising two or three frequencies was more linear and accurate than the traditional peak time and decay coefficient of PECT. Experiments were conducted to validate the results of the simulations and to test the mixed feature in aluminum plate thickness evaluations. The experimental results also revealed that the use of more frequencies did not always increase the accuracy of thickness evaluations. Proper frequency component selection was more efficient than blindly increasing frequency numbers.

Porosity inspection in directed energy deposition additive manufacturing based on transient thermoreflectance measurement

Abstract: In additive manufacturing, material melting-solidification often introduces defects like porosity, lack-of-fusion, delamination, and crack. Such defects are detrimental to the mechanical properties and quality of the manufactured component. In this study, a transient thermoreflectance (TTR) technique using a femtosecond laser is used for porosity inspection in directed energy deposition (DED) additive manufacturing. First, a femtosecond laser TTR measurement system is developed for noncontact measurement of thermoreflectance from a deposited layer. Subsequently, porosity is inspected by comparing the thermoreflectance measured at different pump excitation modulation frequencies. Due to this variation in modulation frequency, the developed porosity inspection technique is rendered sensitive to porosity rather than thermal property variation. Owing to the noncontact nature and scanning capability of the proposed TTR technique, it can be readily applied to in-situ porosity monitoring during DED additive manufacturing. Validation tests were performed on Ti–6Al–4V samples additively manufactured with different printing parameters. The results highlight the feasibility of the proposed technique for in-situ monitoring of porosity in DED additive manufacturing.

Using ResNets to perform automated defect detection for Fluorescent Penetrant Inspection

Abstract: 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.

3D-printed phononic crystal waveguide transducers for nonlinear ultrasonic damage detection

Abstract: Nonlinear ultrasonic methods typically measure second harmonic waves for a rapid and sensitive detection of material micro-cracks. However, fictitious second harmonics generated by the ultrasonic equipment can interfere with signal measurements, causing poor damage detection. This paper aims at enhancing the damage sensitivity of nonlinear ultrasound by developing acrylic phononic crystal waveguide transducers using Polyjet additive manufacturing, which can filter out undesired nonlinear harmonic waves. These sensing devices consist of traditional piezoelectric sensors surface bonded on periodically corrugated structures. Such periodicity can induce stop band frequencies in which the propagation of ultrasonic waves is inhibited. Nonlinear ultrasonic tests confirmed the filtering capabilities of phononic crystal transducers to suppress harmonics created by the ultrasonic instrumentation, thus enabling second harmonic detection on a damage aluminium plate. These results pave the way for simpler, automatable and more accurate nonlinear ultrasonic inspection systems.

Thickness measurement of circular metallic film using single-frequency eddy current sensor

Abstract: In many advanced industrial applications, the thickness is a critical index, especially for metallic coatings. However, the variance of lift-off spacing between sensors and test pieces affects the measured voltage or impedance, which leads to unreliable results from the sensor. Massive research works have been proposed to address the lift-off issue, but few of them applies to the thickness measurement of planar metallic films with finite-size circular (disk) geometry. Previously, a peak-frequency feature from the swept-frequency inductance was used to compensate the measurement error caused by lift-offs, which was based on the slow-changing rate of impedance phase term in the Dodd-Deeds formulas. However, the phase of measured impedance is nearly invariant merely on a limited range of sample thicknesses and working frequencies. Besides, the frequency sweeping is time-consuming, where a recalibration is needed for different sensor setups applied to the online real-time measurement. In this paper, a single-frequency algorithm has been proposed, which is embedded in the measurement instrument for the online real-time retrieval of thickness. Owing to the single-frequency measurement strategy, the proposed method does not need to recalibrate for different sensor setups. The thickness retrieval is based on a triple-coil sensor (with one transmitter and two receivers). The thickness of metallic disk foils is retrieved from the measured electrical resistance of two transmitter-receiver sensing pairs. Experiments on materials of different electrical conductivities (from direct current), thicknesses and planar sizes (radii) have been carried out to verify the proposed method. The error for the thickness retrieval of conductive disk foils is controlled within 5% for lift-offs up to 5 mm.

Fiber bundle tracking method to analyze sheet molding compound microstructure based on computed tomography images

Abstract: Discontinuous fiber reinforced polymers (DicoFRP) like Sheet Molding Compounds (SMC) are frequently applied in modern lightweight designs, due to their good formability and mechanical properties at low density. The DicoFRP microstructure affects the mechanical properties and has to be taken into account in the design process. X-ray Micro-Computed Tomography (μCT) systems acquire volumetric images of microstructures in a non-destructive way. The fiber orientation is determined by using state-of-the-art image processing tools. The resolution of volumetric images and the specimen size are directly coupled due to the cone-beam μCT geometry. In order to identify all individual fibers, high resolution images are needed and consequently, only small specimen volumes are scanned. The present contribution makes use of the property that fibers are arranged as bundles within SMC. Consequently, fiber bundles instead of individual fibers are used to analyze microstructures in order to overcome the μCT-cone-beam-related conflict between sample size and image resolution. The fiber bundles are determined by means of orientation data and an introduced tracking method, facing the challenge of crossing fiber bundles. Subsequently, the tracked fiber bundles, which are related to the same mesoscopic fiber bundle are merged by using a hierarchical agglomerative clustering method. The presented method is applied to a typical SMC microstructure. This contribution introduces an image processing method for analyzing SMC microstructures based on fiber bundles, opening up the possibility to investigate large specimen volumes. This enables to characterize representative SMC microstructures and utilize the data for art modeling approaches.

Novel non-destructive technique for detecting the weld fusion zone using a filler wire of high x-ray contrast

Abstract: Non-destructive testing (NDT) of welded aluminium (Al) joints for quality assessment is of great importance to the automotive industry, among others. Currently, no post-process NDT technique can differentiate between the fusion zone and substrate for typical welded Al joints, thereby preventing measurement of crucial quality metrics such as weld penetration. X-ray Computed Tomography (CT) and x-ray radiography are two common NDT techniques used to evaluate internal discontinuities in welds. A novel method that provides contrast between the Al substrate and weld fusion zone in x-ray images is demonstrated. The post-process technique relies on incorporation of a dopant element in the filler wire with a greater x-ray attenuation coefficient than the substrate, demonstrated here through incorporation of Cu in the filler wire for gas tungsten arc welded (GTAW) Al joints. This novel grayscale contrast in the post-process x-ray images enables the detection of penetration depth and weld throat, which cannot be differentiated when using conventional filler wires. Composition maps of the joint cross sections are compared with the post-process x-ray scans to further examine this technique.

Merging experiments and computer simulations in X-ray Computed Tomography probability of detection analysis of additive manufacturing flaws

Abstract: X-ray Computed Tomography (XCT) is a growing industrial non-destructive testing (NDT) technique for advanced manufacturing industries such as additive manufacturing (AM). Probability of detection (POD) is a critical aspect for qualifying NDT techniques/processes. We present a methodology to empirically determine XCT POD using a two-piece phantom, and which incorporates uncertainty in the measurements of the true flaw size in the phantoms. We additionally demonstrate an application of an XCT full simulation model using simulated phantoms to supplement the experimental measurements. A signal response POD analysis ( a ˆ vs a ) was implemented, where the signal response ( a ˆ ) was the number of voxels determined to be in the flaw, and the true flaw sizes ( a ) were the measured volumes of the flaws. Phantoms with flaws representing AM lack of fusion (LOF) pores were developed and were measured with an optical measurement system allowing the quantification of uncertainty in the measurement of the true flaw size ( a ). The XCT simulations considered factors not assessed by the experimental measurements. The simulated phantoms have various flaw sizes, locations, and orientations. The XCT simulation results were integrated with the experimental results using a multi-level Bayesian model, which incorporated the effects of reference measurement uncertainty, imaging thresholds, and flaw locations and orientations.

Detection of circumferential cracks in heat exchanger tubes using pulsed eddy current testing

Abstract: Heat exchanger tubes in industrial pressure vessels typically require periodic inspection, and detection of circumferential cracks is one of the foremost issues. In this study, the pulsed eddy current method was used for the detection, and new types of probes were designed. Transverse probes were designed to render the eddy currents perpendicular to circumferential cracks to improve detection sensitivity, and the corresponding numerical simulations showed that the eddy currents were approximately perpendicular to the circumferential cracks along more than half of the tube circumference. Thus, two probes could cover the entire circumference for more economical inspection to be achieved. The experiments were performed on copper and steel tubes. The results show that when compared to longitudinal probes, the designed transverse probes significantly improved the detection sensitivity towards circumferential cracks. Particularly, the effectiveness of the proposed method is shown regarding detection of deep defects with good sensitivity in steel tubes without saturation magnetization.

A dual-dipole model for stress concentration evaluation based on magnetic scalar potential analysis

Abstract: Experiment shows that the normal component and the amplitude of the spontaneous magnetic signals on the surface of the ferromagnetic part, induced by a stress concentration zone (SCZ) caused by local plastic deformation, have only one peak. These waveform characteristics are precisely opposite of the defect identification criteria proposed by the metal magnetic memory (MMM) method, which include that the normal component of magnetic signals changes to its polarity and the tangential component reaches a peak value. At the beginning, a magnetic dual-dipole model is accordingly proposed to describe and evaluate the stress concentration in ferromagnetic materials. The contour maps of the magnetic scalar potential show that there is a magnetic source generated in the damaged area. This source can be simplified as a dual-dipole. It comes from the two peaks of stress variation at the edges of the SCZ. Furthermore, the maximum potential of magnetic anomalies was obtained. The values are influenced by the applied loading and deflection of the specimen. It decays exponentially with the increase of lift-off values in the air domain. Finally, residual stresses along the scanning line were measured to confirm the theoretical analysis. This dual-dipole model in the MMM technique is feasible to evaluate the stress concentration caused by local plastic deformation.

Ultrasonic tomographic reconstruction of local fiber orientation in multi-layer composites using Gabor filter-based information diagram method

Abstract: Fiber waviness and ply stacking errors compromise the mechanical performance of multi-layer composites. Measuring the local in-plane fiber orientation layer-by-layer is therefore important to assure the structural integrity of a composite. The Radon transform and the Gabor filter methods have been reported to be appropriate for extracting the fiber orientation from an ultrasonic dataset, where the Radon transform method was found to be more accurate and stable. This paper proposes a tomographic reconstruction method on the basis of classical ultrasound pulse-echo testing, in view of reconstructing the local in-plane fiber orientation in multi-layer composites. A 3D ultrasonic dataset is first sliced successively through depth, and each 2D slice is locally analyzed by a Gabor filter method coupled to the concept of an Information Diagram (GF-ID). The GF-ID improves the Gabor filter method by constructing local Gabor filters with optimal orientation and wavelength from which the local in-plane fiber orientations can be obtained in an automated way. The performance of the developed GF-ID method is investigated on both synthetic texture images and an experimental ultrasonic dataset obtained from a 24-layer [45/0/-45/90]3S carbon fiber reinforced composite. It is found that the GF-ID method yields a high-quality tomographic reconstruction of the local orientations at different scales, and shows high noise resistance. Comparison with the classical Radon transform approach reveals the higher performance of the GF-ID method for ultrasonic reconstruction of the local in-plane fiber orientation in multi-layer composites.

Magnetic incremental permeability as indicator of compression stress in low-carbon steel

Abstract: The field dependences of the signal of induction transducer U~(H), proportional to the magnetic incremental permeability, were obtained on plastically deformed samples of low-carbon steel subjected to compression in the range of elastic deformation. It was found that the greater the relative elongation of the samples, the greater the magnetic fields in which maxima in the U~(H) curves are observed. The additional elastic compression results in the presence of three maxima in the U~(H) curves instead of two. These maxima are associated with the displacement of 90° and 180° domain walls. Most likely, for small values of compressive stresses in the samples, the third maximum in the U~(H) curves was not visible because of its close position to the maximum in the negative field. Fittings by pseudo-Voigt functions were carried out to determine the fields corresponding to three maxima. A new approach was proposed for the evaluation of internal stresses via determination of the fields of two maxima in the U~(H) curve associated mainly with the displacement of 90° domain walls.

Scattering characteristics of quasi-Scholte waves at blind holes in metallic plates with one side exposed to water

Abstract: Corrosion is one of the major issues in metallic structures, especially those operating in humid environments and submerged in water. It is important to detect corrosion at its early stage to prevent further deterioration and catastrophic failures of the structures. Guided wave-based damage detection technique is one of the promising techniques for detecting and characterizing damage in structures. In water-immersed plate structures, most of the guided wave modes have strong attenuation due to energy leakage into the surrounding liquid. However, there is an interface wave mode known as quasi-Scholte waves, which can propagate with low attenuation. Therefore, this mode is promising for structural health monitoring (SHM) applications. This paper presents an analysis of the capability of quasi-Scholte waves in detecting internal corrosion-like defects in water-immersed structures. A three-dimensional (3D) finite element (FE) model is developed to simulate quasi-Scholte wave propagation and wave scattering phenomena on a steel plate with one side exposed to water. The accuracy of the model is validated through experimental measurements. There is good agreement between the FE simulations and experimental measurements. The experimentally verified 3D FE model is then employed in a series of parametric studies to analyze the scattering characteristics of quasi-Scholte waves at circular blind holes with different diameters and depths, which are the simplest representation of progressive corrosion. The findings of this study can enhance the understanding of quasi-Scholte waves scattering at corrosion damage of structures submerged in water and help improve the performance of in-situ damage detection techniques.

Variational level set and fuzzy clustering for enhanced thermal image segmentation and damage assessment

Abstract: One of fundamental steps in the infrared thermographic process is the accurate segmentation of defects displayed on thermal images. State-of-the art segmentation algorithms are still inefficient to background noise, which may cause poor damage detection. In this study, an infrared image segmentation algorithm combined with artificial intelligence-based technology such as the variational level set and fuzzy clustering algorithm is proposed to enhance the quality of thermal images for damage assessment. Local Shannon entropy and fuzzy membership functions are introduced into the external clustering energy in order to make the algorithm robust to the clustering segmentation of noisy images. A higher-order derivative edge detection operator is used in the regularization energy to solve the singularity in the evolution of the level set function. An internal penalty energy is also introduced into the energy functional to avoid the re-initialization of the level set function and reduce the computational time. Experimental results on thermographic data are shown to demonstrate the efficiency and robustness of the proposed methodology.

Maximal overlap discrete wavelet-packet transform aided microwave nondestructive testing

Abstract: The capability of microwave signals to penetrate inside composites and interact with the inner structure makes them a very attractive candidate for composite inspection. Various techniques of microwave nondestructive testing (NDT) are used for detecting disbonds in composites. Despite their promising results, these techniques suffer from poor spatial resolution due to the given features that do not significantly distinguish between the defect and defect-free regions. In this paper, a hybrid signal processing based on a refinement feature extraction method is employed to enhance the imaging efficiency of the disbond detection in composite material. This technique is based on scanning the composite material with an open-ended rectangular waveguide operating from 18 to 26.5 GHz and analyzing its reflections using the proposed hybrid signal processing method. Maximal overlap discrete wavelet packet transform is employed to provide significant informative features of each frequency point. The Bi-directional long short-term memory (Bi-LSTM) network approach is used to distinguish the significant features and the outliers. The Bi-LSTM classifies each inspected location into a defect or defect-free location. The findings presented in this paper show the advantages of the refinement method-aided microwave technique in detecting disbonds down to 1 mm with an accuracy rate of 88.84%, a significant advantage over any current disbond inspection technique.

Integral equation fast solver with truncated and degenerated kernel for computing flaw signals in eddy current non-destructive testing

Abstract: In this article, the kernel independent H -matrix method is applied as the mathematical framework. The dense matrix generated by the selected integral equation, without low frequency breakdown problem for solving 3D arbitrary shaped eddy current nondestructive evaluation (NDE) forward problems, is compressed by the truncated and degenerated (TD) kernel function method. It results in a significant reduction in computational burden with nearly linear complexity. The kernel functions (Green's function) are degenerated by Lagrange polynomials which leads to two advantages: firstly, the double integrals are separated in two single integrals, and secondly, they are represented in a factorized form with good accuracy control. Meanwhile, due to the nature of the kernel function with exponential decay in the lossy medium, it is truncated to improve the overall performance. The TD kernel function-based boundary element method (BEM) fits well for solving eddy current NDE problems over the adaptive cross approximation based BEM, especially for detections of flaws or slots in planar objects. Several numerical predictions calculated by the proposed method are compared with those achieved by others such as the experiment, analytical and semi-analytical methods from benchmarks. The robustness and efficiency are demonstrated with excellent agreements and reduced complexity.

A high-frequency phase feature for the measurement of magnetic permeability using eddy current sensor

Abstract: Electromagnetic sensing has been used for diverse applications of non-destructive testing, including the surface inspection, measurement of properties, object characterization. However, the measurement accuracy could be significantly influenced by the lift-off between sensors and samples. To address the issue caused by lift-offs, various strategies have been proposed for the permeability measurement of ferromagnetic steels, which mainly involves different sensor designs and signal features (e.g., the zero-crossing feature). In this paper, a single high-frequency scenario for the permeability retrieval is introduced. By combining the signal of two sensing pairs, the retrieval of magnetic permeability is less affected by the lift-off of sensors. Unlike the previous strategy on reducing the lift-off effect (directly taking the phase term out of the integration) using the Dodd-Deeds analytical method, the proposed method is based on a high-frequency linear feature of the phase term. Therefore, this method has the merit of high accuracy and fast processing for the permeability retrieval (a simplified version of Dodd-Deeds analytical formulas after the integration). Experimental measurement has been carried out on the impedance measurement of designed sensors interrogating ferromagnetic dual-phase steels. For sensor lift-offs of up to 10 mm, the error of the permeability retrieval is controlled within 4% under the optimal frequency.

Comparison of electromagnetic inspection methods for creep-degraded high chromium ferritic steels

Abstract: Nondestructive testing (NDT) techniques are used to evaluate the material degradation of ferromagnetic materials, for example, in sensitive environments, such as thermal power plants, where the materials are subjected to creep damage. There is no consensus on the use of an electromagnetic NDT technique to characterize the evolution of creep damage in high-chromium ferritic steels. In this work, an overview and comparison of three different electromagnetic NDT techniques that were applied to high-chromium steels is provided to understand creep evolution in terms of microstructural changes, such as precipitation, dislocation and grain size. To quantify the empirical measurements, a modelling technique was proposed for each applied method. The model parameters were optimized for each NDT technique and tested material. Depending on the model parameters, the accuracy of the parameter determination depends strongly on the NDT technique, which indicates its correlation with the microstructural information.

Unidirectional emission and detection of Lamb waves based on a powerful and compact coils-only EMAT

Abstract: This study investigated a compact noncontact electromagnetic acoustic transducer (EMAT) without bulky magnets or separate electromagnets for unidirectional transmission and reception of ultrasonic Lamb waves in 1 mm thick steel plates. The transducer head consists of only two, closely adjacent and elongated flat coils. The powerful sensor technology bridged air gaps up to 1.5 mm. Two phase-adjusted 1 MHz pulses at 1 kV amplitude enhanced the sideways-projected ultrasound field in one direction; others were attenuated by destructive interference. A 5 mm ultrasound wavelength with 1 mm thick steel plate was used for testing; wave field calculations were in good agreement with results. As a possible application, an inaccessible edge of a steel plate was scanned, where the difficulty was increased by an additional edge at a similar distance representing competing interfering reflections. More general progress beyond this specific non-contact application is the demonstration of phase-accurate ultrasound transmission and sensitive echo reception with a compact system of mutually coupling inductors at high power and continuous high-bias currents (1 kA), allowing compact and powerful EMAT phased arrays based on single-layer densely arranged coils.