Search Results (239)

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

In this research, an analysis of the thermomagnetic properties of a nanoscale spin-2 and spin-3/2 system is conducted. This system is modeled with as a quasi-spherical Ising-type nanoparticle with a diameter of 2 nm, in which atoms with spin-2 and spin-3/2 configured in body-centered cubic (BCC) lattices interact within their relevant nanostructures. To determine the thermomagnetic behaviors of the nanoparticle, numerical simulations using Monte Carlo techniques and thermal bath class algorithms are performed. The results exhibit the effects of exchange couplings ($J_1,J_2^{\prime }$), magnetocrystalline anisotropies ($D_{3/2}^{\prime },D_2^{\prime }$), and external magnetic fields ($h^{\prime }$) on the finite-temperature phase diagrams of magnetization ($M_T$), magnetic susceptibility (${\chi }_T$), and thermal energy ($k_B{T}^{\prime }$). The influences of the exchange, anisotropic, and external field parameters are clearly reflected in the compensation, hysteretic, and pseudocritical phenomena presented by the quasi-spherical nanoparticle. When the parameter reflecting ferromagnetic second-neighbor exchanges in the nanosphere ($J_2^{\prime }$) increases, for a given value of the external magnetic field, the compensation ($T_{comp}$) and pseudocritical ($T_{pc}$) temperatures increase. Similarly, in the ranges $0<J_2^{\prime }⩽4.5$ and $-15⩽h^{\prime }⩽15$ at a specific temperature, an increase in $J_2^{\prime }$ results in the appearance of exchange anisotropies (exchange bias) and and increased hysteresis loop areas in the nanomodel. Full article

This paper presents the design, fabrication, calibration, and comprehensive characterization of a homemade tri-axial fluxgate magnetometer. The magnetometer, utilizing a ring core configuration, was developed to measure ultra-low magnetic fields with high sensitivity and stability. Critical stages from material selection to sensor geometry optimization are discussed in detail. A series of critical characterization processes were conducted, including zero-field voltage determination, scale factor calculation, resolution measurement, noise analysis, bias assessment, cross-field effect evaluation, temperature dependency, and bandwidth determination. The sensor demonstrated a minimum detectable magnetic field resolution of 2.2 nT with a noise level of 1.1 nT/√Hz at 1 Hz. Temperature dependency tests revealed minimal impact on sensor output with a maximum shift of 120 nT in the range of 60 °C, which was effectively compensated through calibration to less than 5 nT. Additionally, the paper introduces a model function in matrix form to relate the magnetometer’s output voltage to the measured magnetic field, incorporating temperature dependency and cross-field effects. This work highlights the importance of meticulous calibration and optimization in developing fluxgate magnetometers suitable for various applications, from space exploration to biomedical diagnostics. Full article

Atomic magnetometers based on the spin-exchange relaxation-free (SERF) regime have broad applications in bio-magnetic measurement due to their high sensitivity and miniaturized size. In this paper, we propose a SERF-based magnetometer using 1 × 2 polarization-maintaining fiber (PMF) with single-beam parameter optimization. The impacts of temperature, pumping laser power, and modulation amplitude on the magnetometer’s response signal at the SERF regime are examined. Moreover, through the simulation of zero-field resonance, the compensation accuracy is optimized. To further improve the compensation stability and accuracy, a novel finite state machine (FSM)-assisted iterative optimization magnetic field compensation algorithm is proposed. A pT-level compensation resolution with an error below 1.6% is achieved, which lays the foundation for the subsequent application of biomagnetic measurement arrays. Full article

Wide-speed regulation control strategies for Interior Permanent Magnet Synchronous Motors (IPMSMs) are widely applied in industrial fields. However, traditional algorithms are prone to being affected by motor parameter mismatches, sensor sampling errors, and other disturbances under complex operating conditions, leading to insufficient robustness. In order to enhance dynamic performance while simultaneously ensuring robustness, we analyzed the limitations of traditional control strategies and, based on this, proposed an improved control framework. A Multi-Axis Coordinated Extended State Observer(MCESO)-based robust control framework was developed for full-speed domain operation, which enhances disturbance rejection capability against parameter uncertainties and abrupt load changes through hierarchical disturbance estimation. Subsequently, the effectiveness and stability of the proposed method were verified through theoretical analysis and simulation studies. Compared with traditional control strategies, this method can effectively observe and compensate for a series of complex issues such as nonlinear disturbances during operation without requiring additional hardware support. Finally, extensive experimental tests were carried out on a 500 W IPMSM dual-motor drive platform. The experimental results demonstrated that, even under harsh operating conditions, the proposed scheme can effectively suppress torque ripple and significantly reduce current harmonics. Full article

Accurate current sensing in rectangular conductors is challenged by mechanical deformations, including eccentricity (X/Y-axis shifts) and inclination (Z-axis tilt), which distort magnetic field distributions and induce measurement errors. To address this, we propose a bio-inspired error compensation strategy integrating an elliptically configured Hall sensor array with a hybrid Grey Wolf Optimizer (GWO)-enhanced backpropagation neural network. The eccentric displacement and tilt angle of the conductor are quantified via a three-dimensional magnetic field reconstruction and current inversion modeling. A dual-stage optimization framework is implemented: first, establishing a BP neural network for real-time conductor state estimations, and second, leveraging the GWO’s swarm intelligence to refine network weights and thresholds, thereby avoiding local optima and enhancing the robustness against asymmetric field patterns. The experimental validation under extreme mechanical deformations (X/Y-eccentricity: ±8 mm; Z-tilt: ±15°) demonstrates the strategy’s efficacy, achieving a 65.07%, 45.74%, and 76.15% error suppression for X-, Y-, and Z-axis deviations. The elliptical configuration reduces the installation footprint by 72.4% compared with conventional circular sensor arrays while maintaining a robust suppression of eccentricity- and tilt-induced errors, proving critical for space-constrained applications, such as electric vehicle powertrains and miniaturized industrial inverters. This work bridges bio-inspired algorithms and adaptive sensing hardware, offering a systematic solution to mechanical deformation-induced errors in high-density power systems. Full article

Aeromagnetic detection is a geophysical exploration technology that utilizes aircraft-mounted magnetometers to map variations in the Earth’s magnetic field. As a critical methodology for subsurface investigations, it has been extensively applied in geological mapping, mineral resource prospecting, hydrocarbon exploration, and engineering geological assessments. However, the metallic composition of aircraft platforms inherently generates magnetic interference, which significantly distorts the measurements acquired by onboard magnetometers. Aeromagnetic compensation aims to mitigate these platform-induced magnetic disturbances, thereby enhancing the accuracy of magnetic anomaly detection. Building upon the conventional Tolles-Lawson (T-L) model, this study introduces an enhanced compensation framework that addresses two key limitations: (1) minor deformations that occur due to the non-rigidity of the aircraft fuselage, resulting in additional interfering magnetic fields, and (2) coupled interference between geomagnetic field variations and aircraft maneuvers. The proposed model expands the original 18 compensation coefficients to 57 through dynamic parameterization, achieving a 22.41% improvement in compensation efficacy compared with the traditional T-L model. Furthermore, recognizing the operational challenges of large unmanned aerial vehicles (UAVs) in conventional calibration flights, this work redesigns the flight protocol by eliminating high-risk yaw maneuvers and optimizing the flight path geometry. Experimental validations conducted in the South China Sea demonstrate exceptional performance, with the interference magnetic field reduced to 0.0385 nT (standard deviation) during level flight, achieving an improvement ratio (IR) of 4.1688. The refined methodology not only enhances compensation precision but also substantially improves operational safety for large UAVs, offering a robust solution for modern aeromagnetic surveys. Full article

To address the measurement accuracy degradation of triaxial magnetometers caused by manufacturing errors and environmental interference, and the limited robustness of traditional calibration methods, this study proposes a Dynamic Hierarchical Elite-guided Particle Swarm Optimization (DHEPSO)-based ellipsoid fitting algorithm. First, an error model for the triaxial magnetometers is established. Next, the DHEPSO algorithm is utilized to fit the ellipsoid parameters by integrating a dynamic hierarchical mechanism, elite guidance strategy, and adaptive inertia weight adjustment, thereby balancing global exploration and local exploitation to efficiently optimize the parameters. Finally, error compensation and precise calibration are achieved using the optimized parameters. The simulation results show that, compared to the Least Squares Method (LSM), it reduces the absolute distance between the simulated data and the ellipsoid by 63.10% and the post-calibration total magnetic field intensity standard deviation by 60% under outlier interference. Against the traditional PSO, TSLPSO, MPSO, and AWPSO, DHEPSO achieves total distance reductions of 48.52%, 47.74%, 56.71%, and 33.09%, respectively, with faster convergence. The statistical analysis of 60 trials confirms DHEPSO’s stability, exhibiting lower median error and interquartile range. The results validate DHEPSO’s high precision and robustness in high-noise environments, offering theoretical support for engineering applications. Full article

In finite-size scaling analyses of critical phenomena, proper consideration of correction terms, which can come from different sources, plays an important role. For the Fortuin–Kasteleyn representation of the Q-state Potts model in two dimensions, although the subleading magnetic scaling field, with exactly known exponent, is theoretically expected to give rise to finite-size-scaling analyses, numerical observation remains elusive, probably due to the mixing of various corrections. We simulate the O(n) loop model on the hexagonal lattice, which is in the same universality class as the $Q=n^2$ Potts model but has suppressed corrections from other sources and provides strong numerical evidence for the attribution of the subleading magnetic field in finite-size corrections. Interestingly, it is also observed that the corrections in small- and large-cluster-size regions have opposite magnitudes, and, for the special $n=2$ case, they compensate with each other in observables like the second moment of the cluster-size distribution. Our finding reveals that the effect of the subleading magnetic field should be taken into account in finite-size-scaling analyses, which was unfortunately ignored in many previous studies. Full article

We have developed a miniaturized magnetic sensor based on diamond nitrogen-vacancy (NV) centers, combined with a two-dimensional scanning setup that enables imaging magnetic samples with millimeter-scale resolution. Using the lock-in detection scheme, we tracked changes in the NV’s spin resonances induced by the magnetic field from target samples. As a proof-of-principle demonstration of magnetic imaging, we used a toy diorama with hidden magnets to simulate scenarios such as the remote detection of landmines on a battlefield or locating concealed objects at a construction site, focusing on image analysis rather than addressing sensitivity for practical applications. The obtained magnetic images reveal that they can be influenced and distorted by the choice of frequency point used in the lock-in detection, as well as the magnitude of the sample’s magnetic field. Through magnetic simulations, we found good agreement between the measured and simulated images. Additionally, we propose a method based on NV vector magnetometry to compensate for the non-zero tilt angles of a target, enabling the accurate localization of its position. This work introduces a novel imaging method using a scanning miniaturized magnetometer to detect hidden magnetic objects, with potential applications in military and industrial sectors. Full article

Recent experiments have reported distinct handedness of spin waves across the compensation temperatures of ferrimagnets, offering promising functionalities for ferrimagnet-based magnonic applications with two distinct polarizations. This paper investigates the effects of various factors on the compensation points of GdFe ferrimagnets through atomistic-level spin dynamics simulations. The results show that as the Gd composition increases, both the magnetization compensation temperature and the angular momentum compensation temperature of the GdFe alloy increase, with a linear relationship observed between the two compensation temperatures. Furthermore, we show that external magnetic fields and antiferromagnetic exchange strength can also modulate the compensation temperatures. Moreover, the antiferromagnetic exchange strength also affects the resonance frequency of ferrimagnetic materials. In the absence of an external field, the resonance frequency of GdFe is divided into two branches and both increase linearly with the increase in antiferromagnetic exchange strength. This study may stimulate fundamental research on compensated ferrimagnets, which may be useful for building chirality-based spintronics. Full article

We investigated the hysteresis, pseudo-critical, and compensation behaviors of a quasi-spherical FeCo alloy nanoparticle (2 nm in diameter) using Monte Carlo simulations with thermal bath-type algorithms and a 3D mixed Ising model. The nanostructure was modeled in a body-centered cubic lattice (BCC) through the following configurations: spin $S=3/2$ for Co and $Q=2$ for Fe. These simulations reveal that, under the influence of crystal and magnetic fields, the nanoparticle exhibits compensation phenomena, exchange bias, and pseudo-critical temperatures. Knowledge of this type of phenomena is crucial for the design of new materials, since compensation temperatures and exchange bias improve the efficiency of advanced magnetic devices, such as sensors and magnetic memories. Meanwhile, pseudo-critical temperatures allow the creation of materials with controlled phase transitions, which is vital for developing technologies with specific magnetic and thermal properties. An increase in single-ion anisotropies within the nanosystem leads to higher pseudo-critical and compensation temperatures, as well as superparamagnetic behavior at low temperatures. Full article

For the waveguide coil in a High-Power Microwave (HPM) source, a strong repetitive Flat-top Pulsed Magnetic Field (FTPMF) is needed, which requires the power supply system to generate a high load current (3∼5 kA) with high stability (<1000 ppm) and a long pulse-width (15∼20 ms). To achieve this, this article proposes a novel topology which includes a capacitor bank as the main power supply to guarantee a long pulse-width, combined with an active current compensator to regulate the load current precisely. A PI control scheme with slope compensation is used to solve the current fluctuation caused by capacitor switching. The novel topology also features a fast rising and falling time, thus it is suitable for repetitive working applications. The parameters of the topology are calculated by analysis to guarantee the working condition of a 45 GHz HPM source, and the operating principle of this topology is verified through low-power-scale experiments. Full article

Exchange bias (EB) materials, whose magnetization curve can shift along the field axis after field cooling, have attracted tremendous attention and play a crucial role in the development of fundamental physics as well as practical applications of magnetization storage. In this work, the N-, P-, and Q-type ferrimagnets of Néel’s notation were realized in mixed valence metal formates [CH₃NH₂CH₃]_n[Cr^III_1−xFe^III_xFe^II(HCO₂)₆]_n by altering x, respectively. The positive and negative EB was found in N- and P-type ferrimagnets. The exchange anisotropy originates from the antiferromagnetic exchange interaction between the uncompensated spin of the host ferrimagnetic lattice and the pinned compensated spin of the antiferromagnetic clusters as a guest, which is rooted in the valence disorder of the iron ions. Full article

Airborne magnetic anomaly detection is an important passive remote sensing technique. However, since the magnetic field caused by the aircraft interferes with the detection accuracy, this part of interference should be eliminated by an aeromagnetic compensation method. Most existing compensation methods assume that the ambient magnetic field is uniform when calculating the compensation model parameters. However, as the ambient magnetic field is actually not uniform and varies with the aircraft location, the solved parameters ignore the part of aircraft interference related to the varied ambient magnetic field. Although some of the latest deep learning-based aeromagnetic compensation methods avoid the assumption of uniformity of the ambient magnetic field, the insufficient supervision leads to a poor model generalization. To address these limitations, we propose a self-supervised compensation method. The proposed method utilizes a network to separate the total measured magnetic field into the ambient magnetic field part and the aircraft magnetic field part. By doing so, the method avoids the influence of the uniform ambient magnetic field assumption and enhances the model generalization. In addition, we introduce an improvement ratio loss function to distinguish the aircraft magnetic field from the ambient magnetic field when updating the model parameters. The proposed method is verified using measurement data from real flights. The experimental results indicate that the proposed method significantly outperforms state-of-the-art methods in real flights compensation. Full article