Magnetic Field Data Research Articles

A Non-Contact AI-Based Approach to Multi-Failure Detection in Avionic Systems

The increasing electrification and integration of advanced controls in modern aircraft designs have significantly raised the number and complexity of installed printed circuit boards (PCBs), posing new challenges for efficient maintenance and rapid failure detection. Despite self-diagnostic features in current avionics systems, circuit damage and multiple simultaneous failures may arise, compromising safety and diagnostic accuracy. To address these challenges, this paper aims to develop a fast, accurate, and non-destructive, multi-failure diagnosis algorithm for PCBs. The proposed method combines a self-attention mechanism with an adaptive graph convolutional neural network to enhance diagnostic precision. A convolutional neural network with residual connections extracts features from scalar magnetic field data, ensuring robust input diversity. The model was tested on a typical dual-phase amplitude boosting circuit with up to four different simultaneous failures, achieving the experimental results of 99.08%, 98.50%, 98.78%, 98.01%, 98.93%, 98.25%, 97.03%, and 99.77% across metrics including overall precision, per-class precision, overall recall, per-class recall, overall F1 measure, and per-class F1 measure. The results demonstrated its effectiveness and feasibility in diagnosing complex PCBs with multiple failures, indicating the algorithm’s potential to improve failure diagnosis performance and offer a promising PCB diagnosis solution in aerospace applications.

Crystal structure and magnetic properties of Yb2Pt2Pb under multi-extreme conditions

ABSTRACT Structural and magnetic properties of the Shastry-Sutherland material Yb2Pt2Pb were studied in single-crystalline form under pressures up to 10 GPa, magnetic fields up to 17 T, and temperatures down to 0.3 K. Surprisingly robust magnetic order is observed with the Néel temperature T N = 2.1 K stable up to 8.1 GPa. Indication of an additional magnetic phase formation can be traced in resistivity data for magnetic field along the c-axis exceeding the (pressure-dependent) metamagnetic transition. The related anomaly shifts to higher temperatures with increasing field, merging T N at the tricritical point. Experiments with μ0 H // [110] revealed the pressure stabilization of observed magnetic phases with respect to the magnetic field. The crystal-structure type is stable up to 10 GPa, without any sign of symmetry change, exhibiting moderate volume compressibility with bulk modulus B = 116(13) GPa, in good agreement with B = 118 GPa provided by the density functional theory.

Research on defect image inversion method based on multiple lift-off values magnetic memory signals

Metal magnetic memory (MMM) technique can detect macroscopic defects and stress concentration zones of ferromagnets, and it can identify the approximate positions of these flaws, while a little further information about defects characteristics can be provided. To promote study in this area, defects were modeled as located magnetic dipoles whose strength and locations should be determined, and the technique of truncated generalized inverse and reduced space inversion were used to image the dipole strength. Through the simulation experiment, we found that the inversion image quality was influenced by the lift-off value. When the magnetic field data for inversion was measured with a small lift-off value, the inner dipoles contributions were easily buried and the inversion image can only shown the surface dipole well. In contrast, if the magnetic field data was measured with a greater lift-off value, it was possible to inverse the deep dipoles while the image was somewhat out of focus. To overcome this limitation, we composed the magnetic field data measured under different lift-off values together for inversion. We used the same model to test this approach and applied it on real crack defects magnetic field data. It demonstrates that the new inversion approach shows better accuracy than the single lift-off value and it was possible to infer the location and size of defect by the evaluation of preset dipoles.

Multi-Sensor fusion and semantic map-based particle filtering for robust indoor localization

To enhance positioning accuracy and ensure long-term stability in large-scale indoor environments, this paper presents a robust particle filtering method that integrates IMU, magnetic field, Bluetooth, and semantic map data, implemented through a handheld portable device. In the particle prediction phase, based on peak candidates extracted in the time domain, the unintentional interference movement of the hand is removed through short-time Fourier transform in the frequency domain to reduce the noise of pedestrian dead reckoning. During the observation phase, we introduce a magnetic interference coefficient to model and quantify the degree of electromagnetic interference in different environments, thereby improving the accuracy of indoor magnetic headings and enhancing the alignment of particle swarms with real-world directional constraints. Furthermore, based on passable semantic information, the indoor map is segmented into distinct probability regions, allowing the particle filter to adaptively adjust the weight of the particle swarm when moving between regions, thus improving the robustness of the overall fusion system by preventing particles from entering infeasible areas. Experiments and validations were carried out in a large shopping mall and parking lot with multiple devices. Results demonstrate that the proposed method improves the average positioning accuracy by approximately 25% compared to the Bluetooth-only positioning system, with a 15% increase in cumulative distribution probability within 3 m.

Systematic simulation of tumor cell invasion and migration in response to time-varying rotating magnetic field.

Cancer invasion and migration play a pivotal role in tumor malignancy, which is a major cause of most cancer deaths. Rotating magnetic field (RMF), one of the typical dynamic magnetic fields, can exert substantial mechanical influence on cells. However, studying the effects of RMF on cell is challenging due to its complex parameters, such as variation of magnetic field intensity and direction. Here, we developed a systematic simulation method to explore the influence of RMF on tumor invasion and migration, including a finite element method (FEM) model and a cell-based hybrid numerical model. Coupling with the data of magnetic field from FEM, the cell-based hybrid numerical model was established to simulate the tumor cell invasion and migration. This model employed partial differential equations (PDEs) and finite difference method to depict cellular activities and solve these equations in a discrete system. PDEs were used to depict cell activities, and finite difference method was used to solve the equations in discrete system. As a result, this study provides valuable insights into the potential applications of RMF in tumor treatment, and a series of in vitro experiments were performed to verify the simulation results, demonstrating the model's reliability and its capacity to predict experimental outcomes and identify pertinent factors. Furthermore, these findings shed new light on the mechanical and chemical interplay between cells and the ECM, offering new insights and providing a novel foundation for both experimental and theoretical advancements in tumor treatment by using RMF.

Applicability of Bernoulli's theorem to upstream and downstream of the bow shock

In this research, the validity of Bernoulli's theorem for the solar wind crossing the Earth's bow shock has been investigated based on space explorations. Using solar wind plasma and interplanetary magnetic field data from the OMNI database, along with magnetosheath plasma and magnetic field data measured by the magnetospheric multiscale satellite in 2016 and 2018, 95 events were selected to study the Bernoulli invariant from the upstream to the downstream of Earth's bow shock (from the unshocked solar wind region to the shocked magnetosheath region). Statistical investigations show that the differences in the characteristic energy of plasmas between the solar wind region and the magnetosheath region are less than 5%, regardless of the upstream solar wind speed and the satellite's location in the magnetosheath. These results quantitatively support the generalization of Bernoulli's equation to the solar wind flowing through the bow shock, including the contribution of magnetic field energy.

Data-driven MHD Simulation of the Formation of a Magnetic Flux Rope and an Inclined Solar Eruption

Solar energetic events are caused by the release of magnetic energy accumulated in the solar atmosphere. To understand their initiating physical mechanisms, the dynamics of the coronal magnetic fields must be studied. Unfortunately, the dominant mechanisms are still unclear due to a lack of direct measurements. Numerical simulations based on magnetohydrodynamics (MHD) can reproduce the dynamical evolution of solar coronal magnetic field, providing a useful tool to explore flare initiation. Data-driven MHD simulations, in which the time-series observational data of the photospheric magnetic field is used as the simulation boundary condition, can explore different mechanisms. To investigate the accumulation of free magnetic energy through a solar eruption, we simulated the first of several large flares in NOAA active region 11283. We used a data-driven model that was governed by zero-beta MHD, focusing on the free magnetic energy accumulation prior to the M5.3 flare (2011 September 6 at 01:59 UT). We reproduced the flare-associated eruption following the formation of twisted magnetic fields, or a magnetic flux rope (MFR), formed by photospheric motions at its footpoints. We found that the eruption was first triggered by the growth of the torus instability. The erupting MFR caused magnetic reconnections with neighboring magnetic field lines located along the direction of the eruption. Using the simulation results and an axial-radial decay index centered on the MFR, we find a natural explanation for the inclination of the eruption and a possible approach to predict the direction of solar eruptive events.

Waves and Instabilities in Saturn's Magnetosheath: 1 Mirror Mode Waves and Their Impact on Magnetopause Reconnection

AbstractA comprehensive catalog of 1,589 Saturn magnetosheath traversals by Cassini between 2004 and 2012 was used to perform a statistical study of mirror mode (MM) waves and assess their role in influencing magnetic reconnection at the magnetopause (MP). MM waves have been observed in many planetary magnetospheres and magnetosheaths, comets and the solar wind. Understanding the conditions under which they grow and dominate can reveal their role in influencing plasma dynamics. Using a thresholding method on both magnetic field and plasma data, MM wave candidates can be identified. The magnetic field characteristics and occurrence distributions of these waves against different locations and conditions were found. MM waves were found from 4 to 19 hr local time (partly due to data coverage), and distances of 0–12 from the magnetopause (MP). The occurrence of MM dips was more frequent near the MP and magnetosheath flanks, analogous to the Jovian system. MM dips exhibited a minimum field strength saturation 0.5 nT, with the largest dip inferred to be in mirror‐stable plasma. Notably, larger amplitude MM dips were typically found nearer the MP boundary which increases across the boundary thus increasing the magnetic shear necessary for the onset of MP reconnection. Thus, MM waves may be important in plasma dynamics near Saturn's magnetopause.

Plasmoids and Magnetic Field Dipolarizations During Juno's First 47 Orbits: Is Ion Acceleration Always Observed in the Dipolarizations?

AbstractPlasmoids and magnetic field dipolarizations are reconnection‐related phenomena often resulting in reconfiguration of the magnetic field and energetic particle acceleration in planetary magnetotail. Building on the work of Blöcker et al. (2023) (10.1029/2023JA031312), we selected seven specific events from their magnetic field dipolarization analysis, each exhibiting distinct ion dynamics during the time interval of the magnetic field dipolarizations. To gain further insights into the understanding why certain events were associated with ion intensity variations while others were not, we analyzed plasma moments, specifically ion flow velocity and density, for these selected events. Our findings revealed that certain magnetic field dipolarizations within our database exhibit sub‐Alfvénic flows and lack the properties typically associated with reconnection‐related magnetic field dipolarizations. These magnetic field dipolarizations also do not accelerate ions. Furthermore, we present a survey of Jovian plasmoids and magnetic field dipolarizations during the first 47 orbits of Juno. Applying Juno magnetic field data, we identified 119 magnetic field dipolarizations and 94 plasmoids within a local time range of 18:00–06:00. The majority of plasmoids were detected in the predawn sector, whereas magnetic field dipolarizations were observed closer to Jupiter and were not limited to a specific local time. Combining the statistics of plasmoids and dipolarizations is useful for contextualizing them within the framework of reconnection.

Inducing alternating magnetic fields for real-time non-contact fault localization within electric energy storage component arrays.

With the wide application of electric energy storage component arrays, such as battery cell arrays, capacitor arrays, and inductor arrays, their potential safety risks have gradually drawn the public attention. However, existing technologies cannot realize rapid, precise, and nondestructive localization of the faulty component within these large-scale arrays, especially for a component with an early stage short-circuit fault. To address this challenge, this paper proposes a magnetic field based method and realizes precise fault localization by inducing an alternating magnetic field from the target array, unlike previous research where a static magnetic field was induced. Through establishing a physical model of the short-circuit component as well as the whole array, a spatial filtering algorithm based on beamforming techniques is utilized to process the measured magnetic field data in real time. Both the simulation and experimental results demonstrate the capability of the proposed method in enhancing the security of electric energy storage component arrays. Within an imaging area of 80 × 80 mm2, the proposed method can accurately locate the faulty component out of a nine-component array, with an error of only 0.72mm for capacitors and 0.91mm for battery cells.

Interparticle interaction effect on superparamagnetic properties of ferrimagnetic particles

Uncoated and oleic acid coated ferrimagnetic particles are synthesized. Both samples contain similar magnetite particles. Structural characterization of these particles is performed using x-ray diffraction, Fourier transform infrared spectra, dynamic light scattering, transmission electron microscopy and thermogravimetric analysis. Average crystallite size of magnetite is 7 nm. Thickness of oleic acid layer on each magnetite particle is 1 nm. The oleic acid coated sample contains 23% oleic acid. Temperature dependence of the zero field cooled and field cooled susceptibility of the uncoated magnetite particles peaks at 120 K and both the curves bifurcate at 195 K. The peak temperature and the bifurcation temperature of the system decrease due to the oleic acid coating. The inverse susceptibility does not vary linearly with temperature in high temperature region. Magnetization versus applied magnetic field data at 250 K are analyzed in three different ways to study the interparticle interaction and the particle size distribution effects on magnetization. We find that the both factors affect the magnetization process of ferrimagnetic nanoparticles.

Spectral properties of solar wind plasma flux and magnetic field fluctuations across fast reverse interplanetary shocks

We have analyzed spectra of fluctuations in the solar wind plasma flux and the magnetic field magnitude near the front of a fast reverse shocks, using data from the BMSW device (Bright Monitor of Solar Wind) operating on the SPEKTR-R satellite. Its time resolution made it possible to study plasma flux fluctuations up to a frequency of 16 Hz. Magnetic field data was taken mainly from the WIND satellite, for which the frequency of the fluctuations considered was up to 5.5 Hz. The slope of the spectra of the solar wind flux fluctuations on MHD scales has been shown to be close to the slope of the spectrum of magnetic field fluctuations in the disturbed region. On kinetic scales, the difference can be significant. For the region ahead of the front, the difference in the slope of the spectrum can be quite large both in the MHD and in the kinetic region. The frequency of the break of the flux spectrum ranges from 0.6 to 1.3 Hz, which corresponds to the scale of the proton inertial length. In a number of events, however, the shape of the spectrum indicates the influence of the proton gyroradius frequency, which is usually 0.05–0.15 Hz. The break in the power spectrum of magnetic field fluctuations also more often ranges from 0.7 to 1.2 Hz. In this case, the slope of the MHD part of the spectrum changes little, but in the kinetic part it increases slightly when moving to the disturbed region.

Анализ спектров флуктуаций величины потока плазмы и модуля магнитного поля на обратных ударных волнах

We have analyzed spectra of fluctuations in the solar wind plasma flux and the magnetic field magnitude near the front of a fast reverse shocks, using data from the BMSW device (Bright Monitor of Solar Wind) operating on the SPEKTR-R satellite. Its time resolution made it possible to study plasma flux fluctuations up to a frequency of 16 Hz. Magnetic field data was taken mainly from the WIND satellite, for which the frequency of the fluctuations considered was up to 5.5 Hz. The slope of the spectra of the solar wind flux fluctuations on MHD scales has been shown to be close to the slope of the spectrum of magnetic field fluctuations in the disturbed region. On kinetic scales, the difference can be significant. For the region ahead of the front, the difference in the slope of the spectrum can be quite large both in the MHD and in the kinetic region. The frequency of the break of the flux spectrum ranges from 0.6 to 1.3 Hz, which corresponds to the scale of the proton inertial length. In a number of events, however, the shape of the spectrum indicates the influence of the proton gyroradius frequency, which is usually 0.05–0.15 Hz. The break in the power spectrum of magnetic field fluctuations also more often ranges from 0.7 to 1.2 Hz. In this case, the slope of the MHD part of the spectrum changes little, but in the kinetic part it increases slightly when moving to the disturbed region.

Custom integration of a magnetic-field monitoring system into a 32-channel MRI head coil.

Customizing a Siemens 32-channel coil for use in a Philips 3T MRI system with incorporated magnetic field probes for collecting high-quality MRI and magnetic-field monitoring data concurrently. The development process of the custom coil involved several (iterative) phases. Standard temporal SNR and B1 + data were collected with the 32-channel Siemens and for reference the 32-channel/8-channel Philips head coils before and afterthe custom coil was made compatible with the 3T Philips Achieva system, and magnetic field probes were installed into it along with ancillary electronics around it. Quality assurance tests were conducted in each of the build phases to ensure that the modifications did not affect MRI or field-monitoring data negatively. To test the finished custom coil, we collected high angular resolution diffusion imaging (HARDI) datasets on a spherical silicon oil phantom both with and without concurrent field monitoring and a 32-channel Philips coil without concurrent field monitoring, where the latter two served as reference scans to assess the improved performance of the custom coil with field monitoring. Similar HARDI-MRI data were also collected in vivo with the finished custom coil together with field monitoring data. The custom coil provided excellent temporal SNR especially at the edges where cortical gray matter is expected. When using concurrent field monitoring in HARDI acquisitions, the custom coil alleviated ghosting artifacts in phantom data and provided in vivo images with 1.4-mm isotropic resolution. The custom MRI coil with integrated magnetic-field monitoring probes provided improved imaging performance.

Magnetosonic waves in the Martian ionosphere driven by upstream proton cyclotron waves: Two-point observations by MAVEN and Mars Express

Recent observations from the Mars Atmosphere and Volatile EvolutioN (MAVEN) and Mars Express (MEX) spacecraft have suggested that pressure pulses originating from upstream proton cyclotron waves (PCWs) can “ring” the Martian magnetopause at the same frequency and drive magnetosonic waves in the upper ionosphere of Mars, thereby transporting energy from the solar wind into the ionosphere. However, the limitation of single-spacecraft measurements prevents simultaneous observations of the driver and response of this “ringing” process of the Martian magnetosphere. Here we utilize two-point measurements from MAVEN and MEX to characterize the ringing probability at which upstream PCWs drive compressional fluctuations in the ionospheric magnetic field. We develop an algorithm to identify PCW-driven magnetosonic waves in the upper ionosphere of Mars from the two-point magnetic field data. The derived ringing probability is higher on the dayside, outside strong crustal magnetic fields, and under high solar wind density conditions. We also show that the median power of dayside ionospheric magnetic field fluctuations is enhanced by a factor of ∼2 at corresponding frequencies in the presence of upstream PCWs compared to the median power in the absence of upstream PCWs. These results demonstrate the prevalence of energy deposits into the dayside Martian ionosphere from the solar wind mediated by the PCW-driven ringing of the magnetosphere. Future studies, possibly with new multi-point observations, should address the detailed processes of wave propagation and energy transport through the system and the long-term impact of this chain of processes on the planetary ion heating in the ionosphere and atmospheric loss from Mars.

Citizen science: Development of a low-cost magnetometer system for a coordinated space weather monitoring

As part of Ham Radio Science Citizen Investigation (HamSCI) Personal Space Weather Station (PSWS) project, a low-cost, commercial off-the-shelf magnetometer has been developed to provide quantitative and qualitative measurements of the geospace environment from the ground for both scientific and operational purposes at a cost that will allow for crowd-sourced data contributions. The PSWS magnetometers employ a magneto-inductive sensor technology to record three-axis magnetic field variations with a field resolution of ∼3 nT at a 1 Hz sample rate. The measurement range of the sensor is ±1.1×106 nT) and is valid over a temperature range of −40 °C to +85 °C. Data from the PSWS network will combine these magnetometer measurements with high frequency (HF, 3–30 MHz) radio observations to monitor large-scale current systems and ionospheric disturbances due to drivers from both space and the atmosphere. A densely-spaced magnetometer array, once established, will demonstrate their space weather monitoring capability to an unprecedented spatial extent. Magnetic field data obtained by the magnetometers installed at various locations in the US are presented and compared with the existing magnetometers nearby, demonstrating that the performance is very adequate for scientific investigations.

Generalized Time‐Series Analysis for In Situ Spacecraft Observations: Anomaly Detection and Data Prioritization Using Principal Components Analysis and Unsupervised Clustering

AbstractIn situ spacecraft observations are critical to our study and understanding of the various phenomena that couple mass, momentum, and energy throughout near‐Earth space and beyond. However, on‐orbit telemetry constraints can severely limit the capability of spacecraft to transmit high‐cadence data, and missions are often only able to telemeter a small percentage of their captured data at full rate. This presents a programmatic need to prioritize intervals with the highest probability of enabling the mission's science goals. Larger missions such as the Magnetospheric Multiscale mission (MMS) aim to solve this problem with a Scientist‐In‐The‐Loop (SITL), where a domain expert flags intervals of time with potentially interesting data for high‐cadence data downlink and subsequent study. Although suitable for some missions, the SITL solution is not always feasible, especially for low‐cost missions such as CubeSats and NanoSats. This manuscript presents a generalizable method for the detection of anomalous data points in spacecraft observations, enabling rapid data prioritization without substantial computational overhead or the need for additional infrastructure on the ground. Specifically, Principal Components Analysis and One‐Class Support Vector Machines are used to generate an alternative representation of the data and provide an indication, for each point, of the data's potential for scientific utility. The technique's performance and generalizability is demonstrated through application to intervals of observations, including magnetic field data and plasma moments, from the CASSIOPE e‐POP/Swarm‐Echo and MMS missions.

Testing the Efficacy of Indirect Methods on Characterization of Sedimentary Basins by Correlation of Direct Data and Geophysical Techniques

The information obtained from direct data (geological mapping and boreholes) and indirect techniques (reflection seismology, time-domain electromagnetics and magnetometry) is combined to analyse the northern limit of the Bailén basin (southeastern Spain). This Triassic–Neogene basin is confined by a graben-type structure, limited by two normal faults in the SW–NE direction (the Baños de la Encina-La Carolina fault and Guarromán fault). The movement of these faults was complex, with different pulses occurring over time. Therefore, the subsidence of the basin and the sedimentary filling of the graben were different, giving rise to lateral changes in the facies and thicknesses. This study focuses on the Baños de la Encina fault, chosen as the experimental site to analyse the effectiveness and accuracy of these geophysical techniques to reveal the basement structure and geometry. Seismic reflection allows to detect two faults that caused the subsidence of the eastern sector of the graben. The TDEM method made it possible to calculate the depth of the Palaeozoic basement, as well as reveal the presence of the two aforementioned faults. Magnetic total field data highlight variations in the basement depth that can be used to infer previously unknown fractures, in this case, in the NW–SE direction.

Development of Precision Controllable Magnetic Field-Assisted Platform for Micro Electrical Machining.

In order to introduce the magnetic field into micro electrical machining technology to explore the influence of magnetic field on micro electrical machining, the development of a precision controllable magnetic field-assisted platform is particularly important. This platform needs to precisely control the spatial magnetic field. This study first completes the hardware design and construction of the magnetic field generation device, using electromagnetic coils with soft iron cores as the sources of the magnetic field. Mathematical models of the magnetic field are established and calibrated. Since the magnetic dipole model cannot effectively describe the magnetic field generated by the electromagnetic coil, this study adopts a more precise description method: the spherical harmonic function expansion model and the magnetic multipole superposition model. The calibration of the magnetic field model is based on actual excitation magnetic field data, so a magnetic field sampling device is designed to obtain the excitation magnetic field of the workspace. The model is calibrated based on a combination of the theoretical model and magnetic field data, and the performance of the constructed setup is analyzed. Finally, a magnetic field-assisted platform has been developed which can generate magnetic fields in any direction within the workspace with intensities ranging from 0 to 0.2 T. Its magnetic field model arrives at an error percentage of 2.986%, a variance of 0.9977, and a root mean square error (RMSE) of 0.71 mT, achieving precise control of the magnetic field in the workspace.

Modeling Soft X‐Ray Emissions at the Dayside Magnetopause

AbstractIn this study, we simulate the Solar Wind Charge Exchange (SWCX) soft X‐ray emissions at dayside magnetosheath and cusps by using magnetohydrodynamic (MHD) and LAtmos TEst Particle (LaTeP) models. MHD models are unable to resolve the particle kinetic effects, such as the different behaviors of ions with different q/m, or distinguish the magnetospheric plasma from the solar wind plasma. We investigate these effects with the LaTeP model. As the LaTeP model does not self‐compute magnetic and electric field, the magnetic and electric field data obtained from Open Geospace General Circulation Model (OpenGGCM) and Lagrangian version of the piecewise parabolic method (PPMLR) MHD model are used as the input to LaTeP model. The soft X‐ray emissivity maps simulated from pure OpenGGCM and PPMLR MHD approaches and from LaTeP‐OpenGGCM and LaTeP‐PPMLR approaches are presented and compared. The results indicate that the LaTeP model can well resolve the kinetic effects and can be used to investigate the individual spectral characteristics. Therefore, the LaTeP model is a complementary approach for simulating the X‐ray emissions near the dayside magnetopause. We also calculate the ratio of integrated OVII/OVIII line intensities, produced by charge exchange of O7+ ions and O8+ ions, respectively. We find a relatively higher ratio at the bow shock compared to the surrounding areas, suggesting that this ratio can be an effective parameter to identify the bow shock location.