Spherical echo-planar time-resolved imaging (sEPTI) for rapid 3D quantitative T 2 * and susceptibility imaging.

PURPOSE: To develop a 3D spherical EPTI (sEPTI) acquisition and a comprehensive reconstruction pipeline for rapid high-quality whole-brain submillimeter T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification. METHODS: For the sEPTI acquisition, spherical k-space coverage is utilized with variable echo-spacing and maximum kx ramp-sampling to improve efficiency and signal incoherency compared to existing EPTI approaches. For reconstruction, an iterative rank-shrinking B0 estimation and odd-even high-order phase correction algorithms were incorporated into the reconstruction to better mitigate artifacts from field imperfections. A physics-informed unrolled network was utilized to boost the SNR, where 1-mm and 0.75-mm isotropic whole-brain imaging were performed in 45 and 90 s at 3 T, respectively. These protocols were validated through simulations, phantom, and in vivo experiments. Ten healthy subjects were recruited to provide sufficient data for the unrolled network. The entire pipeline was validated on additional five healthy subjects where different EPTI sampling approaches were compared. Two additional pediatric patients with epilepsy were recruited to demonstrate the generalizability of the unrolled reconstruction. RESULTS: sEPTI achieved 1.4 × $$ \times $$ faster imaging with improved image quality and quantitative map precision compared to existing EPTI approaches. The B0 update and the phase correction provide improved reconstruction performance with lower artifacts. The unrolled network boosted the SNR, achieving high-quality T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification with single average data. High-quality reconstruction was also obtained in the pediatric patients using this network. CONCLUSION: sEPTI achieved whole-brain distortion-free multi-echo imaging and T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification at 0.75 mm in 90 s which has the potential to be useful for wide clinical applications.

Eddy Current-Based Identification and Depth Investigation of Microdefects in Steel Filaments.

In the field of quality control, the critical challenge of analyzing microdefects in steel filament holds significant importance. This is particularly vital, as steel filaments serve as reinforced fibers in the use and applications within various component manufacturing industries. This paper addresses the crucial requirement of identifying and investigating microdefects in steel filaments. Eddy current signals are used for the identification of microdefects, and an in-depth investigation is conducted. The core objective is to establish the relationship between the depth of defects and the signals detected through the eddy current sensing principle. The threshold of the eddy current instrument was set at 10%, corresponding to a created depth of 20 µm, to identify defective specimens. A total of 30 defective samples were analyzed, and the phase angles between the experimental and theoretical results were compared. The depths of defects ranged from 20 to 60 µm, with one sample having a depth exceeding 75 µm. The calculated threshold of 10.18% closely aligns with the set threshold of 10%, with a difference of only 1.77%. The resulting root mean square error (RMSE) was found to be 10.53 degrees, equivalent to 3.49 µm for the difference in depth and phase between measured results and estimated results. This underscores the methodology's accuracy and its applicability across diverse manufacturing industries.

Eddy Current Sensor Probe Design for Subsurface Defect Detection in Additive Manufacturing.

Pore and crack formation in parts produced by additive manufacturing (AM) processes, such as laser powder bed fusion, is one of the issues associated with AM technology. Surface and subsurface cracks and pores are induced during the printing process, undermining the printed part durability. In-situ detection of defects will enable the real-time or intermittent control of the process, resulting in higher product quality. In this paper, a new eddy current-based probe design is proposed to detect these defects in parts with various defects that mimic pores and cracks in additively manufactured parts. Electromagnetic finite element analyses were carried out to optimize the probe geometry, followed by fabricating a prototype. Artificial defects were seeded in stainless steel plates to assess the feasibility of detecting various flaws with different widths and lengths. The smallest defect detected had a 0.17 mm radius for blind holes and a 0.43 mm notch with a 5 mm length. All the defects were 0.5 mm from the surface, and the probe was placed on the back surface of the defects. The surface roughness of the tested samples was less than 2 µm. The results show promise for detecting defects, indicating a potential application in AM.

Magnetic Sensor Angle Adjustment to Improve Corrosion under Insulation Detection.

A large portion of the pipe infrastructure used in the chemical processing industry is susceptible to corrosion under insulation (CUI). Eddy current-based magnetic sensing is one of the methods that can be used as an early detector of this corrosion. However, the large sensor-to-pipe distances used in this method, due to the presence of insulation, limits the sensitivity to corrosion. This paper will describe the development of instrumentation and methods based on eddy current sensing with thin-film magnetic sensors. In particular, it focuses on the influence of the sensor angle relative to the radial magnetic field. The influence of this parameter on the amplitude of the measured signal was investigated by both finite element simulations and experimental observations. The measured magnetic field was found to be highly sensitive to small changes in sensor angle, with the estimated depth of a defect changing at a rate of 11.2 mm/degree of sensor rotation for small angles. It is also shown that a sensor aligned with the radial direction should be avoided, with an optimal sensor angle between 0.5 and 4 degrees. With the sensor in this angle range, the simulations have shown it should be possible to resolve the depth of corrosion to a resolution of 0.1 mm.

Resonant Eddy Current Sensor Design for Corrosion Detection of Reinforcing Steel.

This paper introduces an LC resonator-based single-frequency eddy current (EC) sensor designed for corrosion detection in reinforcing bars (rebars) embedded within concrete structures. The work addresses the challenges of the limited detection ranges and reduced sensitivity over longer distances, prevalent in current EC sensor applications. The sensor development process involved a systematic experimental approach to carefully selecting each parameter in the LC resonator. The sensor design aimed to assess the condition of the rebar from a distance of up to 5-6 cm outside the concrete and provide insights into different corrosion levels. By examining the characteristics of the inductors, the parallel resistance Rp of the eddy current coil was identified as a key parameter reflecting the corrosion conditions in the rebar. The relationship between the Rp fluctuations and temperature variations was investigated, with the data indicating that an approximately 155 Ω variation can be expected per 1 °C change within the temperature range of 20-25 °C, allowing for temperature compensation if necessary. Subsequently, the sensor's performance was evaluated by placing a rebar within a concrete block, where controlled mechanical degradation cycles were applied to simulate uniform corrosion in the rebar. The experimental results show that our EC sensor can detect material loss around the rebar with accuracy of approximately 0.17 mm.

Eddy Current Sensor Array for Electromagnetic Sensing and Crack Reconstruction with High Lift-Off in Railway Tracks.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

Eddy Current Array for Defect Detection in Finely Grooved Structure Using MSTSA Network.

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.

Experimental Investigation on the Effect of Coil Shape on Planar Eddy Current Sensor Characteristic for Blade Tip Clearance.

Given the increasing application of eddy current sensors for measuring turbine tip clearance in aero engines, enhancing the performance of these sensors is essential for improving measurement accuracy. This study investigates the influence of coil shape on the measurement performance of planar eddy current sensors and identifies an optimal coil shape to enhance sensing capabilities. To achieve this, various coil shapes-specifically circular, square, rectangular wave, and triangular wave-were designed and fabricated, featuring different numbers of turns for the experiment at room temperature. By employing a method for calculating coil inductance, the performance of each sensor was evaluated based on key metrics: measurement range, sensitivity, and linearity. Experimental results reveal that the square coil configuration outperforms other shapes in overall measurement performance. Notably, the square coil demonstrated a measurement range of 0 mm to 8 mm, a sensitivity of 0.115685 µH/mm, and an impressive linearity of 98.41% within the range of 0 mm to 2 mm. These findings indicate that the square coil configuration enhances measurement capabilities. The conclusions drawn from this study provide valuable insights for selecting coil shapes and optimizing the performance of planar eddy current sensors, thereby contributing to the advancement of turbine tip clearance measurement techniques in aero engines.

Eddy Current-Based Delamination Imaging in CFRP Using Erosion and Thresholding Approaches.

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.

Numerical Investigation on the Influence of Turbine Rotor Parameters on the Eddy Current Sensor for the Dynamic Blade Tip Clearance Measurement.

Eddy current sensors are increasingly being used to measure the dynamic blade tip clearance in turbines due to their robust anti-interference capabilities and non-contact measurement advantages. However, the current research primarily focuses on enhancing the performance of eddy current sensors themselves, with few studies investigating the influence of turbine rotor parameters on the measurements taken by these sensors for dynamic blade tip clearance. Hence, this paper addresses this gap by using COMSOL Multiphysics 6.2 software to establish a finite model with circuit interfaces. Additionally, the model's validity was verified through experiments. This model is used to simulate the voltage output of the sensor and the measurement of dynamic blade tip clearance under various rotor parameters. The results indicate that the length and number of blades, as well as the hub radius, significantly affect the sensor voltage output in comparison to rotation speed. Furthermore, we show that traditional static calibration methods are inadequate for measuring dynamic blade tip clearance using eddy current sensors. Instead, it is demonstrated that incorporating rotor parameters into the calibration of eddy current sensors can enhance the accuracy of dynamic blade tip clearance measurements.

Non-Destructive Testing of Carbon Fiber-Reinforced Plastics (CFRPs) Using a Resonant Eddy Current Sensor.

Eddy current testing (ECT) is commonly used for the detection of defects inside metallic materials. In order to achieve the effective testing of CFRP materials, increasing the operating frequency or improving the coil structure is a common method used by researchers. Higher or wider operating frequencies make the design of the ADC's conditioning circuit complex and difficult to miniaturize. In this paper, an LC resonator based on inductance-to-digital converters (LDCs) is designed to easily detect the resonant frequency response to the state of the material under test. The reasonableness of the coil design is proven by simulation. The high signal-to-noise ratio (SNR) and detection sensitivity of the LC resonator are demonstrated through comparison experiments involving multiple probes. The anti-interference capability of the LC resonator in CFRP defect detection is demonstrated through various interference experiments.

Classification of Corrosion Severity in SPCC Steels Using Eddy Current Testing and Supervised Machine Learning Models.

Steel Plate Cold-Rolled Commercial (SPCC) steel is known to have long-term durability. However, it still undergoes corrosion when exposed to corrosive environments. This paper proposes an evaluation method for assessing the corrosion level of SPCC steel samples using eddy current testing (ECT), along with two different machine learning approaches. The objective is to classify the corrosion of the samples into two states: a less corroded state (state-1) and a highly corroded state (state-2). Generative and discriminative models were implemented for classification. The generative classifier was based on the Gaussian mixture model (GMM), while the discriminative model was based on the logistic regression model. The features used in the classification models are the peaks of the perturbated magnetic fields at two different frequencies. The performance of the classifiers was evaluated using metrics such as absolute error, accuracy, precision, recall, and F1 score. The results indicate that the GMM model is more conducive to categorizing states with higher levels of corrosion, while the logistic regression model is helpful in estimating states with lower levels of corrosion. Meanwhile, high classification accuracy can be achieved based on both methods using eddy current testing.

Detecting Near-Surface Sub-Millimeter Voids in Additively Manufactured Ti-5V-5Al-5Mo-3Cr Alloy Using a Transmit-Receive Eddy Current Probe.

Additive Manufacturing (AM) Direct Laser Fabrication (DLF) of Ti-5Al-5V-5Mo-3Cr (Ti5553) is being developed as a method for producing aircraft components. The additive manufacturing process can produce flaws near the surface, such as porosity and material voids, which act as stress raisers, leading to potential component failure. Eddy current testing was investigated to detect flaws on or near the surface of DLF Ti5553 bar samples. For this application, the objective was to develop an eddy current probe capable of detecting flaws 500 µm in diameter, located 1 mm below the component's surface. Two initial sets of coil parameters were chosen: The first, based on successful experiments that demonstrated detection of a near surface flaw in Ti5553 using a transmit-receive array probe, and the second, derived from simulation by Finite Element Method (FEM). An optimized transmit receive coil design, based on the FEM simulations, was constructed. The probe was evaluated on Ti5553 samples containing sub-surface voids of the target size, as well as samples with side-drilled holes and samples with holes drilled from the opposing inspection surface. The probe was able to effectively detect 80% of the sub-surface voids. Limitations included the probe's inability to detect sub-surface voids near sample edges and a sensitivity to surface roughness, which produces local changes in lift-off. Multifrequency mixing improved signal-to-noise ratio when surface roughness was present on average by 22%. A probe based on that described in this paper could benefit quality assurance of additively manufactured aircraft components.

Eddy Current Position Measurement in Harsh Environments: A Temperature Compensation and Calibration Approach.

Eddy current displacement sensors (ECDSs) are widely used for the noncontact position measurement of small displacements (lift-offs). Challenges arise with larger displacements as the sensitivity of the ECDSs decreases. This leads to a more pronounced impact of temperature variations on the inductance and, consequently, an increased position error. Design solutions often rely on multiple coils, suitable coil carrier materials, and compensation measures to address the challenges. This study presents a single-coil ECDS for large displacement ranges in environments with high temperatures and temperature variations. The analysis is based on a sensor model derived from an equivalent circuit model (ECM). We propose design measures for both the sensing coil and the target, focusing on material selection to handle the impact of temperature variations. A key part of improving performance under varying temperatures includes model-based temperature compensation for the inductance of the sensing coil. We introduce a method to calibrate the sensor for large displacements, using a modified coupling coefficient based on field simulation data. Our analysis shows that this single-coil ECDS design maintains a position error of less than 0.2% full-scale for a temperature variation of 100 K for the sensing coil and 110 K for the target.

A biogenic hydrogel to recover Au(III) from electronic waste.

In the course of this investigation, we undertook the contemplation of a green chemistry paradigm with the express intent of procuring valuable metal, namely gold, from electronic waste (e-waste). In pursuit of this overarching objective, we conceived a procedural framework consisting of two pivotal stages. As an initial stage, we introduced a physical separation procedure relying on the utilization of the Eddy current separator, prior to embarking on the process of leaching from e-waste. Subsequent to the partitioning of metals from the non-metal constituents of waste printed circuit boards (PCB), we initiated an investigation into the hydrogel derived from basil seeds (Ocimum basilicum L.), utilizing it as a biogenic sorbent medium. The thorough characterization of hydrogel extracted from basil seeds involved the application of an array of analytical techniques, encompassing FTIR, XRD, SEM, and BET. The batch sorption experiments show more than 90% uptake in the pH range of 2-5. The sorption capacity of the hydrogel material was evaluated as 188.44 mg g-1 from the Langmuir Isotherm model. The potential interference stemming from a spectrum of other ions, encompassing Al, Cu, Ni, Zn, Co, Cr, Fe, Mn, and Pb was systematically examined. Notably, the sole instance of interference in the context of adsorption of gold ions was observed to be associated with the presence of lead. The application of the hydrogel demonstrated a commendable efficiency in the recovery of Au(III) from the leached solution derived from the waste PCB.

A 6-DoF position sensor for bearingless slice motors.

This paper describes a position sensor with six degrees of freedom (DoF) measurement capability. This sensor is designed for the position sensing of the rotor in a bearingless slice motor to enable active control. The sensor is designed to fit entirely under the rotor and operates by accessing the rotor bottom surface only, enabling packaging of the pump on the top of the rotor. The sensor has two parts; both operate using eddy currents. One of these parts measures the two radial DoF of the rotor. The other part measures the axial, angular rotation and tip/tilt DoF. The sensor utilizes a conductive target fixed to the underside of the rotor. Motion of this target varies the magnetic fields which can then be measured by the sensor as variation in either induced voltage or inductance value. The design and fabrication of the sensor along with the signal processing methods are presented in detail. The radial position measurements are the most critical for active levitation due to the small working gaps in these DoF, hence a resolution of < 1.2 ​ µ m and bandwidth of 1 kHz is achieved. This paper also describes the closed-loop behavior of a bearingless motor using this sensor.

Robust dual-module velocity-selective arterial spin labeling (dm-VSASL) with velocity-selective saturation and inversion.

PURPOSE: Compared to conventional arterial spin labeling (ASL) methods, velocity-selective ASL (VSASL) is more sensitive to artifacts from eddy currents, diffusion attenuation, and motion. Background suppression is typically suboptimal in VSASL, especially of CSF. As a result, the temporal SNR and quantification accuracy of VSASL are compromised, hindering its application despite its advantage of being delay-insensitive. METHODS: A novel dual-module VSASL (dm-VSASL) strategy is developed to improve the SNR efficiency and the temporal SNR with a more balanced gradient configuration in the label/control image acquisition. This strategy applies for both VS saturation (VSS) and VS inversion (VSI) labeling. The dm-VSASL schemes were compared with single-module labeling and a previously developed multi-module schemes for the SNR performance, background suppression efficacy, and sensitivity to artifacts in simulation and in vivo experiments, using pulsed ASL as the reference. RESULTS: Dm-VSASL enabled more robust labeling and efficient backgroud suppre across brain tissues, especially of CSF, resulting in significantly reduced artifacts and improved temporal SNR. Compared to single-module labeling, dm-VSASL significantly improved the temporal SNR in gray (by 90.8% and 94.9% for dm-VSS and dm-VSI, respectively; P < 0.001) and white (by 41.5% and 55.1% for dm-VSS and dm-VSI, respectively; P < 0.002) matter. Dm-VSI also improved the SNR of VSI by 5.4% (P = 0.018). CONCLUSION: Dm-VSASL can significantly improve the robustness of VS labeling, reduce artifacts, and allow efficient background suppression. When implemented with VSI, it provides the highest SNR efficiency among VSASL methods. Dm-VSASL is a powerful ASL method for robust, accurate, and delay-insensitive perfusion mapping.

Correction of B0 and linear eddy currents: Impact on morphological and quantitative ultrashort echo time double echo steady state (UTE-DESS) imaging.

The purpose of the current study was to investigate the effects of B0 and linear eddy currents on ultrashort echo time double echo steady state (UTE-DESS) imaging and to determine whether eddy current correction (ECC) effectively resolves imaging artifacts caused by eddy currents. 3D UTE-DESS sequences based on either projection radial or spiral cones trajectories were implemented on a 3-T clinical MR scanner. An off-isocentered thin-slice excitation approach was used to measure eddy currents. The measurements were repeated four times using two sets of tested gradient waveforms with opposite polarities and two different slice locations to measure B0 and linear eddy currents simultaneously. Computer simulation was performed to investigate the eddy current effect. Finally, a phantom experiment, an ex vivo experiment with human synovium and ankle samples, and an in vivo experiment with human knee joints, were performed to demonstrate the effects of eddy currents and ECC in UTE-DESS imaging. In a computer simulation, the two echoes (S+ and S-) in UTE-DESS imaging exhibited strong distortion at different orientations in the presence of B0 and linear eddy currents, resulting in both image degradation as well as misalignment of pixel location between the two echoes. The same phenomenon was observed in the phantom, ex vivo, and in vivo experiments, where the presence of eddy currents degraded S+, S-, echo subtraction images, and T2 maps. The implementation of ECC dramatically improved both the image quality and image registration between the S+ and S- echoes. It was concluded that ECC is crucial for reliable morphological and quantitative UTE-DESS imaging.

Methodology for Eddy Current Losses Calculation in Linear Variable Differential Transformers (LVDTs).

Linear variable differential transformer (LVDT) is a commonly used linear displacement sensor because of its good measurement characteristics. When using laminated ferromagnetic cores in LVDTs, it is very important to take eddy currents into the account during design phase of the sensor. Particularity of the open-type core means that the eddy currents induced by the stray magnetic flux that flow in large loops tangential to the lamination surfaces take on significant values. Due to the open-type core a typical LVDT has, depending on the core material, it is, therefore, very important to take eddy currents into the account when designing the sensor. This paper's goal is to present a methodology for calculating LVDT eddy current losses that can be applied to LVDT design in order to optimize the dimensions and help with selection of materials of the LVDTs, in order to achieve the highest measurement accuracy. Presented approach using an AτA-formulation with elimination of redundant degrees of freedom exhibits rapid convergence. In order to calculate the relationship between eddy current losses and core displacement, frequency, and material characteristics, a number of 3D finite element method (FEM) simulations was performed. Analysis of the obtained results using presented methodology for eddy current losses calculation in LVDTs enables the designer optimize the design of the LVDT.

Comparison Research on Characterization and Evaluation Approaches for Paint Coated Corrosion Using Eddy Current Pulsed Thermography.

Paint coated corrosion detection and evaluation is a big challenge for steel performance and structure health. Eddy current pulsed thermography (ECPT) technique is investigated because it can reflect the corrosion physical properties through paint coating by the infrared signal. This paper proposes skewness method, which presents the feature of temperature curve's shape automatically, and compares it with principal component analysis (PCA), phase analysis, and kurtosis feature extraction methods for paint coated corrosion characterization and evaluation. The averaged skewness shows the best sensitivity for 0-6 months corrosion. The normalized second principal component (PC) presents good sensitivity and the best measurement scale for corroded time. Furthermore, the temperature curve analysis proves that the electrical conductivity dominates the induced heating and heat distribution. The corrosion height is utilized to explain why ECPT technique is valid within 10 months corroded time. ECPT technique is proved as a smart sensor system for paint coated corrosion detection and characterization.