Search Results (95)

This study aims to develop a library of Cu-CuAl material compositions and evaluate their mechanical properties. Various compositions are fabricated using Wire Arc Additive Manufacturing (WAAM) with GMAW and GTAW processes. The produced materials are characterised through hardness testing, eddy current measurements, and tensile testing supported by Digital Image Correlation (DIC). The hardness analysis reveals that increasing the CuAl content leads to higher hardness values. All compositions display stable and consistent eddy current measurements, except for the alloy with 25% Cu and 75% CuAl, which shows comparatively higher values. The load–displacement curves indicate that higher Cu content enhances ductility, resulting in a lower maximum load. Conversely, a higher CuAl fraction is directly associated with greater ultimate tensile strength. Overall, compositions with higher CuAl content exhibit improved mechanical performance, although they do not reach the levels of commercial materials due to defects inherent to the additive manufacturing process. Full article

To address the problems of weak geometric features, low signal response amplitude, and insufficient spatial resolvability of near-surface defects in metal substrates, a high-resolution spatiotemporal-coded eddy-current array probe is proposed. The probe adopts an array topology with time-multiplexed excitation and adjacent differential reception, achieving a balance between high common-mode rejection ratio and high-density spatial sampling. First, a theoretical electromagnetic coupling model between the probe and the metal substrate is established, and finite-element simulations are conducted to investigate the evolution of the skin effect, eddy-current density distribution, and differential impedance response over an excitation frequency range of 1–10 MHz. Subsequently, a 64-channel M-DECA probe and an experimental testing platform are developed, and frequency-sweeping experiments are carried out under different excitation conditions. Experimental results indicate that, under a 50 kHz excitation frequency, the array eddy-current response achieves an optimal trade-off between signal amplitude and spatial geometric consistency. Furthermore, based on the pixel-to-physical coordinate mapping relationship, the lateral equivalent diameters of near-surface defects with different characteristic scales are quantitatively characterized, with relative errors of 6.35%, 4.29%, 3.98%, 3.50%, and 5.80%, respectively. Regression-based quantitative analysis reveals a power-law relationship between defect area and the amplitude of the differential eddy-current array response, with a coefficient of determination ${\mathrm{R}}^2=0.9034$ for the bipolar peak-to-peak feature. The proposed M-DECA probe enables high-resolution imaging and quantitative characterization of near-surface defects in metal substrates, providing an effective solution for electromagnetic detection of near-surface, low-contrast defects. Full article

High brittleness severely restricts the practical use of nanocrystalline cores in low-frequency power electronics. To enhance mechanical strength and facilitate cutting and transportation, curing techniques are commonly employed, yet their influence on the magnetic properties of the cores remains unclear. In this work, three curing techniques, namely, fluid-phase adhesive curing, gel-phase adhesive curing, and vacuum-evacuated gel-phase adhesive curing (VGAC), are applied to prepare cores with varying curing degrees. The magnetic properties of them are quantitatively compared with those of uncured cores within the range of 50–550 Hz. Results show that all three curing techniques demonstrably reduce the eddy current losses of the cores. Specifically, the VGAC-based core exhibits a 50% reduction in eddy current loss compared to the uncured core at 550 Hz and 0.8 T. Meanwhile, high saturation flux density is retained in all cured samples. However, curing also reduces permeability and raises coercivity. Furthermore, cured cores demonstrate increased hysteresis and residual losses, leading to higher total losses. The relationship between core losses and temperature rise is also investigated to provide important guidance for the safe operation of cured cores. In addition, microscopic images under 200× magnification are presented to elucidate the mechanisms underlying these observed influences. Full article

Background/Objectives: The glymphatic system plays a crucial role in clearing brain metabolic waste, and its dysfunction has been correlated to various neurological disorders. The Diffusion Tensor Imaging Analysis Along the Perivascular Space (DTI-ALPS) index has been proposed as a non-invasive marker of glymphatic function by measuring diffusivity along perivascular spaces; however, its sensitivity to sleep-related changes in glymphatic activity has not yet been validated. This study aimed to evaluate the feasibility of using the DTI-ALPS index as a quantitative marker of dynamic glymphatic activity during sleep. Methods: Diffusion tensor imaging (DTI) data were obtained from 12 healthy male participants (age = 24.44 ± 2.5 years; Pittsburgh Sleep Quality Index (PSQI) < 5), once while awake and 16 times during sleep, following 24 h sleep deprivation and administration of 10 mg zolpidem. Simultaneous MR-compatible electroencephalography was used to determine whether the subject was asleep or awake. DTI preprocessing included eddy current correction and tensor fitting. The DTI-ALPS index was calculated from nine regions of interest in projection and association areas aligned to standard space. The final analysis included nine participants (age = 24.56 ± 2.74 years; PSQI < 5) who maintained a continuous sleep state for 1 h without awakening. Results: Among nine ROI pairs, three showed significant increases in the DTI-ALPS index during sleep compared to wakefulness (Friedman test; p = 0.027, 0.029, 0.034). These ROIs showed changes at 14, 19, and 25 min after sleep induction, with FDR-corrected p-values of 0.024, 0.018, and 0.018, respectively. Conclusions: This study demonstrated a statistically significant increase in the DTI-ALPS index within 30 min after sleep induction through time-series DTI analysis during wakefulness and sleep, supporting its potential as a biomarker reflecting glymphatic activity. Full article

As the core components of geophysical dynamic system, oceans and atmospheres are dominated by the Coriolis force, which governs complex dynamic phenomena such as internal waves, gravity currents, vortices, and others involving multi-scale spatiotemporal coupling. Due to the limitations of in situ observations, large-scale rotating tanks have emerged as critical experimental platforms for simulating Earth’s rotational effects. This review summarizes recent advancements in rotating tank applications for studying oceanic flow phenomena, including mesoscale eddies, internal waves, Ekman flows, Rossby waves, gravity currents, and bottom boundary layer dynamics. Advanced measurement techniques, such as particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), have enabled quantitative analyses of internal wave breaking-induced mixing and refined investigations of vortex merging dynamics. The findings demonstrate that large-scale rotating tanks provide a controllable experimental framework for unraveling the physical essence of geophysical fluid motions. Such laboratory experimental endeavors in a rotating tank can be applied to more extensive scientific topics, in which the rotation and stratification play important roles, offering crucial support for climate model parameterization and coupled ocean–land–atmosphere mechanisms. Full article

This paper presents a discrete Fourier transform (DFT)-based signal processing framework for eddy current non-destructive testing (NDT), aiming to enhance signal quality for precise defect characterization in critical nuclear components. By enforcing strict periodicity matching between sampling points and signal frequencies, the proposed approach mitigates DFT spectrum leakage, validated via phase linearity analysis with errors of ≤0.07° across the 20 Hz–1 MHz frequency range. A high-resolution 24-bit analog-to-digital converter (ADC) hardware architecture eliminates complex analog balancing circuits, reducing system-wide noise by overcoming the limitations of traditional 16-bit ADCs. A 6 × 6 mm application-specific integrated circuit (ASIC) for array sensors enables three-dimensional (3D) defect visualization, complemented by Gaussian filtering to suppress vibration-induced noise. Our experimental results demonstrate that the digital method yields smoother signal waveforms and superior 3D defect imaging for nuclear power plant tubes, enhancing result interpretability. Field tests confirm stable performance, showcasing clear 3D defect distributions and improved inspection performance compared to conventional techniques. By integrating DFT signal processing, hardware optimization, and array sensing, this study introduces a robust framework for precise defect localization and characterization in nuclear components, addressing key challenges in eddy current NDT through systematic signal integrity enhancement and hardware innovation. Full article

We developed a measurement system capable of detecting magnetic responses in various material samples. The system utilizes an excitation coil to apply an alternating magnetic field within the frequency range of 1–10 kHz. The magnetic field generated in the samples was detected using a highly sensitive magnetoresistive sensor. The system demonstrated a detection lower limit in the sub-pT range for magnetic fields arising from magnetic responses such as eddy currents and magnetization changes. The frequency dependence of the detected signal intensities correlated well with the physical mechanisms underlying the magnetic responses. Notably, the distance between the excitation coil and the magnetic sensor was maintained at 300 mm. These results, which demonstrate the detection of a sub-pT magnetic field using a highly sensitive magnetic sensor, have not been previously reported and provide valuable insights for advancing practical applications in non-destructive testing and clinical diagnostic imaging. Full article

Infrared (IR) magneto-optical (MO) bi-imaging is an innovative method for detecting weld defects, and it is important to process both IR thermography and MO imaging characteristics of weld defects. IR thermography and MO imaging can not only run simultaneously but can also run separately in special welding processes. This paper studies the sensing processing of eddy current IR thermography and MO imaging for detecting weld defects of laser spot welding and butt joint laser welding, respectively. To address the issues of high-level noise and low contrast in eddy current IR detection thermal images interfering with defect detection and recognition, a method based on least squares and Gaussian-adaptive bilateral filtering is proposed for denoising eddy current IR detection thermal images of laser spot welding cracks and improving the quality of eddy current IR detection thermal images. Meanwhile, the image gradient is processed by Gaussian-adaptive bilateral filtering, and then the filter is embedded in the least squares model to smooth and denoise the image while preserving defect information. Additionally, MO imaging for butt joint laser welding defects is researched. For the acquired MO images of welding cracks, pits, incomplete fusions, burn-outs, and weld bumps, the MO image processing method that includes median filtering, histogram equalization, and Wiener filtering was used, which could eliminate the noise in an image, enhance its contrast, and highlight the weld defect features. The experimental results show that the proposed image processing method can eliminate most of the noise while retaining the weld defect features, and the contrast between the welding defect area and the normal area is greatly improved. The denoising effect using the Natural Image Quality Evaluator (NIQE) and the Blind Image Quality Index (BIQI) has been evaluated, further demonstrating the effectiveness of the proposed method. The differences among weld defects could be obtained by analyzing the gray values of the weld defect MO images, which reflect the weld defect information. The MO imaging method can be used to investigate the magnetic distribution characteristics of welding defects, and its effectiveness has been verified by detecting various butt joint laser welding weldments. Full article

Stainless steel core plates (SSCPs) show great potential for modular construction due to their superiority of excellent mechanical properties, light weight, and low cost over traditional concrete and honeycomb structures. During the brazing process of SSCP joints which connect the skin panel and core tubes, it is difficult to keep an even heat flow of inert gas in the vast furnace, which can lead to partially missing solder defects in brazing joints. Pulsed eddy current imaging (PECI) has demonstrated feasibility for detecting missing solder defects, but various factors including lift-off variation and image blurring can deteriorate the quality of C-scan images, resulting in inaccurate evaluation of the actual state of the brazed joints. In this study, a differential pulsed eddy current testing (PECT) probe is designed to reduce the lift-off noise of PECT signals, and a mask-based image segmentation and thinning method is proposed to eliminate the blurring effect of C-scan images. The structure of the designed probe was optimized based on finite element simulation and the positive peak of the PECT signal was selected as the signal feature. Experiments with the aid of a scanning device are then carried out to image the interrogated regions of the SSCP specimen. The peak values of the signals were collected in a matrix to generate images of the scanned brazing joints. Results show that lift-off noise is significantly reduced by using the differential probe. Image blurring caused by the convolution effect of the probe’s point spread function with the imaging object was eliminated using a mask-based image segmentation and thinning method. The restored C-scan images enhance the sharpness of the profiles of the brazing joints and the opening in the images accurately reflect the missing solder of the brazed joints. Full article

This paper presents the development of a novel eddy current array (ECA) system for real-time, layer-by-layer quality control in powder bed fusion (PBF) additive manufacturing. The system is integrated into the recoater of a PBF machine to provide spatially resolved electrical conductivity imaging of the manufactured part. The system features an array of 40 inductive sensors spaced at 1 mm pitch and is capable of performing a full array readout every 0.192 mm at 100 mm/s recoater speed. Array scalability was achieved through the careful selection of the electromagnetic configuration, miniaturized and seamlessly integrated sensor elements, and the use of advanced mixed signal processing techniques. Experimental validation was performed on stainless steel 316L parts, successfully detecting metallic structures and confirming system performance in both laboratory and real-time PBF environments. The prototype achieved a signal-to-noise ratio (SNR) of 26.5 dB, discriminating metal from air and thus demonstrating its potential for improving PBF part design, process optimization, and defect detection. Full article

We present a new method for accurately measuring the aperture of a fluid-driven fracture. This method uses an eddy current probe located within a completion tool specifically designed to obtain the fracture aperture in the wellbore at the location where the fluid is injected into the fracture. The probe induces an eddy current in a target object, producing a magnetic field that affects the overall magnetic field. It does not have any limitations with respect to fluid pressure and temperature within a large range, making it unlike other methods. We demonstrate the accuracy and performance of the sensor under laboratory conditions. A hydraulic fracture experiment in a porous sandstone is conducted and discussed. The obtained measurement of the evolution of the fracture inlet aperture by the eddy current probe during the multiple injection cycles performed provided robust information. The residual fracture aperture (after the test) measured by the probe is in line with estimations from image processing of X-ray CT scan images as well as a thin-section analysis of sub-parts of the fractured specimen. The robustness and accuracy of this electromagnetic induction probe demonstrated herein under laboratory conditions indicate an interesting potential for field deployment. Full article

In this paper, we focus on eddy current array (ECA) technology for defect detection in finely grooved structures of spinning cylinders, which are significantly affected by surface texture interference, lift-off distance, and mechanical dither. Unlike a single eddy current coil, an ECA, which arranges multiple eddy current coils in a specific configuration, offers not only higher accuracy and efficiency for defect detection but also the inherent properties of space and time for signal acquisition. To efficiently detect defects in finely grooved structures, we introduce a spatiotemporal self-attention mechanism to ECA testing, enabling the detection of defects of various sizes. We propose a Multi-scale SpatioTemporal Self-Attention Network for defect detection, called MSTSA-Net. In our framework, Temporal Attention (TA) and Spatial Attention (SA) blocks are incorporated to capture the spatiotemporal features of defects. Depth-wise and point-wise convolutions are utilized to compute channel weights and spatial weights for self-attention, respectively. Multi-scale features of space and time are extracted separately in a pyramid manner and then fused to regress the bounding boxes and confidence levels of defects. Experimental results show that the proposed method significantly outperforms not only traditional image processing methods but also state-of-the-art models, such as YOLOv3-SPP and Faster R-CNN, with fewer parameters and lower FLOPs in terms of Recall and F1 score. Full article

Carbon fiber reinforced plastic (CFRP) is a composite material known for its high strength-to-weight ratio, stiffness, and corrosion and fatigue resistance, making it suitable for its use in structural components. However, CFRP can be subject to various types of damage, such as delamination, matrix cracking, or fiber breakage, requiring nondestructive evaluation to ensure structural integrity. In this context, damage imaging algorithms are important for assessing the condition of this material. This paper presents signal and image processing methods for delamination characterization of thin CFRP plates using eddy current testing (ECT). The measurement system included an inductive ECT probe with three coil elements, which has the characteristic of allowing eddy currents to be induced in the specimen with two different configurations. In this study, the peak amplitude of the induced voltage in the receiver element and the phase shift between the excitation and receiver signals were considered as damage-sensitive features. Using the ECT probe, C-scans were performed in the vicinity of delamination defects of different sizes. The dimensions and shape of the ECT probe were considered by applying the erosion method in the damage imaging process. Different thresholding approaches were also investigated to extract the size of the defective areas. To evaluate the impact of this application, a comparison is made between the results obtained before and after thresholding using histogram analysis. The evaluation of damage imaging for three different delamination sizes is presented for quantitative analysis. Full article

Pulsed eddy current thermography can detect surface or subsurface defects in steel, but in the process of combining deep learning, it is expensive and inefficient to build a complete sample of defects due to the complexity of the actual industrial environment. Consequently, this study proposes a transfer learning method based on Twin-NMF and combines it with the SimAM attention mechanism to enhance the detection accuracy of the target domain task. First, to address the domain differences between the target domain task and the source domain samples, this study introduces a Twin-NMF transfer method. This approach reconstructs the feature space of both the source and target domains using twin non-negative matrix factorization and employs cosine similarity to measure the correlation between the features of these two domains. Secondly, this study integrates a parameter-free SimAM into the neck of the YOLOv8 model to enhance its capabilities in extracting and classifying steel surface defects, as well as to alleviate the precision collapse phenomenon associated with multi-scale defect recognition. The experimental results show that the proposed Twin-NMF model with SimAM improves the detection accuracy of steel surface defects. Taking NEU-DET and GC10-DET as source domains, respectively, in the ECTI dataset, mAP@0.5 reaches 99.3% and 99.2%, and the detection accuracy reaches 98% and 98.5%. Full article

In contrast to conventional non-destructive testing (NDT) and non-destructive evaluation (NDE) methodologies, including radiography, ultrasound, and eddy current analysis, coplanar capacitive sensing technique emerges as a novel and promising avenue within the field. This paper endeavors to elucidate the efficacy of coplanar capacitive sensing, also referred to as capacitive imaging (CI), within the realm of NDT. Leveraging extant scholarly discourse, this review offers a comprehensive and methodical examination of the coplanar capacitive technique, encompassing its fundamental principles, factors influencing sensor efficacy, and diverse applications for defect identification across various NDT domains. Furthermore, this review deliberates on extant challenges and anticipates future trajectories for the technique. The manifold advantages inherent to coplanar capacitive sensing vis-à-vis traditional NDT methodologies not only afford its versatility in application but also underscore its potential for pioneering advancements in forthcoming applications. Full article