Field Magnetic Imaging Research Articles

Design and implementation of a nondestructive testing system for magnetic field imaging based on machine learning

This study presents the design of a nondestructive testing (NDT) system for detecting metal defects using a magnetic field sensor array. The system integrates a hardware-software detection framework that includes parallel computation and processing cores, along with multiple anisotropic magnetoresistance (AMR) sensors. These AMR sensors capture subtle variations in the magnetic field, which serve as the foundation for defect identification. The system enables synchronized data acquisition from multiple AMR sensors, achieving multi-axis data fusion and parallel signal processing. Furthermore, the detection system gathers defect features to train an NDT system based on machine learning (ML). Subsequently, ML-generated defect imaging features are processed through an imaging framework, producing magnetic field imaging (MFI) for precise defect localization. The study tested six different metal samples with various defect sizes and types to validate the system. The results demonstrate the system’s ability to accurately detect and identify different defects, highlighting the high precision of magnetic field detection and the overall effectiveness of the proposed system for NDT.

Utilizing the multifrequency resonances of the electron spins in diamond nitrogen-vacancy centers under strong radio frequency driving for quantum sensing

Multifrequency resonances in the pulsed-optically detected magnetic resonance (ODMR) spectra of electron spins in ensemble nitrogen-vacancy (NV) centers in diamonds are investigated under strong radio frequency (RF) driving at a MHz frequency range and weak microwave driving at a GHz frequency range in a bias static magnetic field for quantum sensing applications. First, we demonstrate that the coherent destruction of tunneling, which leads to the disappearance of the main resonance peaks, can be utilized for precise calibration of the RF amplitude. Next, we clarify the condition for enhancing the sensitivity of a DC magnetic field under strong RF driving at the RF frequency that matches the split frequency due to the hyperfine interaction between 15N nuclear spins and the NV electron spins. Our findings indicate that strong RF driving increases the sensitivity of the DC magnetic field by enhancing the ODMR contrast and reducing the linewidth. The above results contribute to certifying the quantitative accuracy of RF imaging and enhancing the sensitivity of the DC magnetic field imaging using ensemble NV centers in diamonds.

Quantitative magnetooptical analysis using indicator films for the detection of magnetic field distributions, temperature, and electrical currents

The accurate characterization of local magnetic fields and temperature is vital for the design of electronic systems. To meet this imperative, we present a novel non-contact approach for simultaneous quantitative magnetic field imaging and temperature sensing using magnetooptics and a bismuth-doped yttrium iron garnet film with out-of-plane anisotropy. For the direct signal quantification, a Stokes polarization camera is employed in a conventional magnetooptical microscope. The magnetization in the garnet is modulated with an external magnetic field to continuously image the Faraday rotation at four distinct points along the saturating magnetization loop. The method enables sensing of the magnetooptical signal in saturation, the magnetooptical susceptibility, the temperature, and self-calibrated driftfree imaging of the out-of-plane magnetic field component. A spatial resolution of magnetic field in the micrometer range with millisecond exposure time is demonstrated. The method is verified by analyzing the stray magnetic field distribution of electrical current in a wire simultaneously to the Joule heating induced by the applied current.

Direct Magnetic Field Imaging by Advanced Differential Phase Contrast Scanning Transmission Electron Microscopy

Direct Magnetic Field Imaging by Advanced Differential Phase Contrast Scanning Transmission Electron Microscopy

A High-Resolution Magnetic Field Imaging System Based on the Unpackaged Hall Element Array

We have designed a high-resolution magnetic field imaging system using 256 unpackaged Hall elements. These unpackaged Hall elements are arranged in a Hall linear array, and the distance between adjacent elements reaches 255 µm. The sensitivity of the unpackaged Hall element array can be adjusted using a computer to measure magnetic environments with different magnetic field strengths. High-resolution magnetic field images of 256 × 256 pixels can be generated by moving the array using the X–Y axis motorized rail. This spatial resolution can reach 99.61 pixels per inch (ppi). This rail allows for the spatial resolution of the system to be further increased to 199.22 ppi by using a special movement route. In the experiments, we employ this system to image magnetized metal scissors, and the result displays the structural features of the scissor surface. We also detected the magnetic suction wireless charging coil inside an Apple phone. The image obtained shows the shape of the coil and the gap between the magnets. The high-resolution magnetic imaging system displays the magnetic characteristics of the sample very well and easily obtains information about small-shaped structures and defects on the sample surface. This provides the system with potential in several fields such as quality inspection, security, biomedicine, and detection imaging.

Magnetic field analysis and modeling of gradient coils based on ferromagnetic coupling inside magnetically shielded cylinder

To accurately analyze the magnetic field of gradient coils inside a magnetically shielded cylinder (MSC) and enhance the precision of remanence compensation, analytical models for calculating the magnetic field of the gradient coils are proposed. First, the coupling between the high-permeability MSC and the coils is accurately analyzed based on Green’ s function method, magnetic field boundary conditions and image method. Secondly, the current density of four commonly used gradient coils is analyzed, and analytical models for the magnetic fields of these four types of gradient coils are established. Finally, the validity of the analytical models is proved through finite element simulations and experimental tests. The experimental results indicate that within the range of x,z∈−80,80mm (± 0.5R), the analytical values have good consistency with experimental values, and the maximum relative error between the two is only 0.91%. The analytical models will be beneficial to the research on the coil optimization design inside the MSC.

Impact of string connection and contact defects on electrical current distribution in solar cells and modules: A model validated by magnetic field imaging

AbstractModeling of solar modules and their components is essential to quantify geometrical, optical, and electrical losses and to improve the designs and technologies in terms of performance. In most loss analysis models, the current share among the busbars of the solar cell is assumed to be equal since a symmetrical distribution of the metallization is given. The impact of string terminal connection on the current distribution among the ribbons and the resulting changes in ohmic losses has not been studied yet. In this study, a MATLAB model is developed to consider the impact of the string connector terminal position on the current distribution and the ohmic losses in the ribbons and in string connector. The model allows for the analysis of the impact of contact defects scenarios in ribbons and string connectors on the current distribution. Results show that the highest current flows at the closest busbar to the string connector terminal while the current decreases at the busbars farther away from the terminal due to higher ohmic resistance of the current path. The higher the ohmic resistance of the string connector, the more inhomogeneous the current share at busbars. Simulating a 9 busbar M6 half‐cell with 1 × 0.08 mm2 string connector, positioning the string connector terminal at the leftmost or rightmost ribbon results in 0.4 W less power compared to center connection configuration, where the string connector terminal is positioned at the center ribbon. Furthermore, simulation results show that inhomogeneity of current causes about 2.1% reduction in module power compared to the case of evenly distributed cell current, considering a 120‐haf‐cell module with the same string connector. Regarding contact defect analysis, exemplary simulations show the impact of the position of detached ribbons on the power or efficiency loss. Considering left or right connection configuration, detaching the leftmost or rightmost ribbon results in higher power loss compared to other ribbons. Detaching one cell ribbon completely from the string connector results in about 0.2%abs decrease in cell efficiency, while detaching the outer ribbon along all strings of a 120‐half‐cell module results in power loss of about 0.8%. The developed model is validated by performing magnetic field imaging (MFI) measurements, in which the magnetic flux density induced by the current carried by the ribbons is measured.

Three-dimensional electrochemical-magnetic-thermal coupling model for lithium-ion batteries and its application in battery health monitoring and fault diagnosis

Storage batteries with elevated energy density, superior safety and economic costs continues to escalate. Batteries can pose safety hazards due to internal short circuits, open circuits and other malfunctions during usage, hence real-time surveillance and error diagnosis of the battery’s operational state is imperative. In this paper, a three-dimensional model of electrochemical-magnetic field-thermal coupling is formulated with lithium-ion pouch cells as the research focus, and the spatial distribution pattern of the physical field such as magnetic field and temperature when the battery is operational is acquired. Furthermore, this manuscript also investigates the diagnostic methodology for defective batteries with internal short circuits and fissures, that is, the operational state of the battery is evaluated and diagnosed by the distribution of the magnetic field surrounding the battery. To substantiate the method’s practical viability, the present study extends its examination to the 18650-battery pack. We obtained the magnetic field images of the normal operation of the battery pack and the failure state of some batteries and analyzed the relationship between the magnetic field distribution characteristics and the performance of the battery pack, providing a new method for the health monitoring and fault diagnosis of the battery pack. This non-contact method incurs no damage to the battery, concurrently exhibiting elevated sensitivity and extremely rapid response time. Meanwhile, it provides an effective means for non-destructive research on the batteries and can be applied to areas such as battery safety screening and non-destructive testing. This research not only helps to facilitate our understanding of the battery’s operating mechanism, but also provides robust support for safe operation and optimal battery design.

A Nondestructive Method to Evaluate of DC-DC Converters Using Subsurface Magnetic Field Imaging with Pulse Width Modulation

A Nondestructive Method to Evaluate of DC-DC Converters Using Subsurface Magnetic Field Imaging with Pulse Width Modulation

Using a single nitrogen-vacancy center in diamond to detect microwave magnetic field vectors at resonant frequency

This study introduces a method for reconstructing vector microwave magnetic fields using a single nitrogen-vacancy (NV) center in locally strong effective fields with two different orientations in diamond, without the previously required external magnetic field. Due to the varying orientations of the effective fields, NV centers exhibit two distinct sets of switchable ground states. The resonant Rabi oscillations of an NV center in these two distinct states were utilized to reconstruct vector microwave magnetic fields. Remarkably, this technique achieves an angular resolution of 0.02 mrad/Hz. Overcoming the limitations inherent in previous practices of using NV ensembles, this breakthrough has the potential to substantially enhance both the spatial resolution and the sensitivity of microwave magnetic field imaging, a meaningful development for various scientific and technological applications.

Segmentation and Volume Estimation of the Habenula Using Deep Learning in Patients With Depression

BackgroundThe habenula is involved in the pathophysiology of depression. However, its small structure limits the accuracy of segmentation methods, and the findings regarding its volume have been inconsistent. This study aimed to create a highly accurate habenula segmentation model using deep learning, test its generalizability to clinical magnetic resonance imaging, and examine differences between healthy participants and patients with depression. MethodsThis multicenter study included 382 participants (patients with depression: N = 234, women 47.0%; healthy participants: N = 148, women 37.8%). A 3-dimensional residual U-Net was used to create a habenula segmentation model on 3T magnetic resonance images. The reproducibility and generalizability of the predictive model were tested on various validation cohorts. Thereafter, differences between the habenula volume of healthy participants and that of patients with depression were examined. ResultsA Dice coefficient of 86.6% was achieved in the derivation cohort. The test-retest dataset showed a mean absolute percentage error of 6.66, indicating sufficiently high reproducibility. A Dice coefficient of >80% was achieved for datasets with different imaging conditions, such as magnetic field strengths, spatial resolutions, and imaging sequences, by adjusting the threshold. A significant negative correlation with age was observed in the general population, and this correlation was more pronounced in patients with depression (p < 10−7, r = −0.59). Habenula volume decreased with depression severity in women even when the effects of age and scanner were excluded (p = .019, η2 = 0.099). ConclusionsHabenula volume could be a pathophysiologically relevant factor and diagnostic and therapeutic marker for depression, particularly in women.

Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms

Superresolution (SR) aims to increase the resolution of images by recovering detail. Compared to standard interpolation, deep learning-based approaches learn features and their relationships to leverage prior knowledge of what low-resolution patterns look like in higher resolution. Deep neural networks can also perform image cross-calibration by learning the systematic properties of the target images. While SR for natural images aims to create perceptually convincing results, SR of scientific data requires careful quantitative evaluation. In this work, we demonstrate that deep learning can increase the resolution and calibrate solar imagers belonging to different instrumental generations. We convert solar magnetic field images taken by the Michelson Doppler Imager (resolution ∼2″ pixel−1; space based) and the Global Oscillation Network Group (resolution ∼2.″5 pixel−1; ground based) to the characteristics of the Helioseismic and Magnetic Imager (resolution ∼0.″5 pixel−1; space based). We also establish a set of performance measurements to benchmark deep-learning-based SR and calibration for scientific applications.

Design of compact integrated diamond nitrogen–vacancy center quantum probe

An integrated quantum probe for magnetic field imaging is proposed, where the nitrogen–vacancy (NV) center fixed at the fiber tip is located on the periphery of flexible ring resonator. Using flexible polyimide (PI) as the substrate medium, we design a circular microstrip antenna, which can achieve a bandwidth of 140 MHz at Zeeman splitting frequency of 2.87 GHz, specifically suitable for NV center experiments. Subsequently, this antenna is seamlessly fixed at a three-dimensional-printed cylindrical support, allowing the optical fiber tip to extend out of a dedicated aperture. To mitigate errors originating from processing, precise tuning within a narrow range can be achieved by adjusting the conformal amplitude. Finally, we image the microwave magnetic field around the integrated probe with high resolution, and determine the suitable area for placing the fiber tip (SAP).

Wide-field Fourier magnetic imaging with electron spins in diamond

Wide-field magnetic imaging based on nitrogen-vacancy (NV) centers in diamond has been shown the applicability in material and biological science. However, the spatial resolution is limited by the optical diffraction limit (>200 nm) due to the optical real-space localization and readout of NV centers. Here, we report the wide-field Fourier magnetic imaging technique to improve spatial resolution beyond the optical diffraction limit while maintaining the large field of view. Our method relies on wide-field pulsed magnetic field gradient encoding of NV spins and Fourier transform under pixel-dependent spatial filters. We have improved spatial resolution by a factor of 20 compared to the optical resolution and demonstrated the wide-field super-resolution magnetic imaging of a gradient magnetic field. This technique paves a way for efficient magnetic imaging of large-scale fine structures at the nanoscale.

High resolution magnetic field imaging probe with two rows of TMR sensors for small defects inspection

It is still a challenging problem to detect small defects for eddy current array probes, which requires the probes to possess excellent sensitivity, as well as high spatial resolution. This paper presents a novel high-resolution magnetic field imaging probe with two rows of tunneling magnetoresistance (TMR) array sensors. The bare die sensors are integrated on a printed circuit board by golden wire bonding technology. The two rows of sensors are placed staggered with each other. The data of the two arrays are merged into a matrix, in which way the image pixel pitch is increased to 0.25 mm. The probe employs a differential scheme to suppress the noise, so as to detect the weak signal of small defects. To highlight the weak defect indications, feature extraction and segmentation algorithms are developed. The experimental results confirm that the proposed method can inspect a small defect with dimensions 1 mm (length) × 0.1 mm (width) × 0.1 mm (depth) on a stainless-steel sample.

In Situ Inversion of Lithium-Ion Battery Pack Unbalanced Current for Inconsistency Detection Using Magnetic Field Imaging

In Situ Inversion of Lithium-Ion Battery Pack Unbalanced Current for Inconsistency Detection Using Magnetic Field Imaging

High-Performance Chip Design With Parallel Architecture for Magnetic Field Imaging System

High-Performance Chip Design With Parallel Architecture for Magnetic Field Imaging System

Nitrogen-vacancy center magnetic imaging of Fe3O4 nanoparticles inside the gastrointestinal tract of Drosophila melanogaster.

Widefield magnetometry based on nitrogen-vacancy centers enables high spatial resolution imaging of magnetic field distributions without a need for spatial scanning. In this work, we show nitrogen-vacancy center magnetic imaging of Fe3O4 nanoparticles within the gastrointestinal tract of Drosophila melanogaster larvae. Vector magnetic field imaging based on optically detected magnetic resonance is carried out on dissected larvae intestine organs containing accumulations of externally loaded magnetic nanoparticles. The distribution of the magnetic nanoparticles within the tissue can be clearly deduced from the magnetic stray field measurements. Spatially resolved magnetic imaging requires the nitrogen-vacancy centers to be very close to the sample making the technique particularly interesting for thin tissue samples. This study is a proof of principle showing the capability of nitrogen-vacancy center magnetometry as a technique to detect magnetic nanoparticle distributions in Drosophila melanogaster larvae that can be extended to other biological systems.

Using Magnetic Field Analysis for Localizing Defects of Fuel Cell & Electrolyzer Components

Production capacities of electrolysis and fuel cell technologies are expected to increase significantly in the upcoming years, reducing costs of stack components through numbering-up. To ensure reliability and durability and reduce costs along the manufacturing process, developing suitable in-line non-destructive diagnostic methods for quality control becomes essential for their industrialization.In both fuel cell and electrolyzer stacks, the main components' electrical resistance and current density distribution greatly influence stack efficiency and longevity. Here, the flowing electric current generates a magnetic field depending on its strength and direction. Potential defects caused by the manufacturing process, including cracks, defective welding spots, coating adhesion issues, delamination, and contamination, influence the components' electric conductivity and current density distribution and hence the magnetic field distribution.This work investigates non-destructive diagnostic methods using magnetic field analysis (MFA) to identify changes in the magnetic field distribution and, thus, local electrical resistance and current density distributions of fuel cell and electrolyzer components. The methods used are magnetic field imaging (MFI) and Eddy Current Testing (ECT). MFI analyzes the magnetic field distribution in all three spatial directions to trace electrical currents and identify electrical defects, creating a magnetic field signature that can potentially distinguish between functional and non-functional components along the manufacturing process. ECT measures variations in local conductivity by inducing eddy currents in the sample through an alternating magnetic field generated by a sender coil. These eddy currents create a detectable magnetic field in a receiver and are affected by defects and changes in electrical conductivity. Therefore, the method can characterize sheet resistance and material homogeneity through electrical anisotropy in electrically conductive components.In initial experiments, ECT measurements on coated and uncoated hollow embossed stainless steel bipolar half plates showed systematic differences depending on quality characteristics resulting in unique patterns and inhomogeneities which require further investigation. Furthermore, experiments with both methods on other stack components will be presented and discussed. In addition, their in-line capability will be assessed and evaluated. However, these first promising results imply that MFA is potentially useful as an in-line, non-destructive diagnostic method for quality control.

Ultrahigh-resolution Magnetic Field Imaging by Magnetic-field-free Atomic Resolution Electron Microscopy

Ultrahigh-resolution Magnetic Field Imaging by Magnetic-field-free Atomic Resolution Electron Microscopy