Search Results (316)

Series–series (S–S) compensated wireless power-transfer (WPT) systems are increasingly deployed where connector-free and reliable energy delivery is required, but practical monitoring becomes ambiguous when receiver-resonance drift and magnetic-coupling variation produce similar transmitter-side impedance changes. This paper addresses that ambiguity by separating the two effects without receiver-side sensing. During a low-power diagnostic interval, the receiver terminal is briefly placed in open and short states, and only the fundamental phasors of the inverter output voltage and primary current are processed together with the known compensation capacitances. After the open-state measurement identifies the primary self-impedance, the short-state residual is mapped to an affine D–${\omega }^2$ line; its zero crossing gives the receiver resonant frequency and secondary self-inductance, while its slope gives the mutual inductance and coupling coefficient. The routine is implementable as a start-up or periodic diagnostic function in WPT hardware that already measures the primary voltage and current and can impose the required receiver terminal states; it requires no receiver-side measurement, auxiliary sensing coil, short-loop resistance measurement, or iterative zero-phase search. In simulation, the coupling-coefficient error remained below $0.014\%$ under receiver-inductance tolerance and mutual-inductance variation. In a prototype, the short-state data followed the predicted linear relation with $R^2=0.9979$, and the extracted coupling coefficient agreed with the reference within about $5\%$. The identified receiver resonance was also used to guide operating-frequency adjustment in a practical power-transfer test. Full article

The study is driven by its importance in modern material processing and precision engineering, where understanding and controlling interfacial stability is crucial in maintaining reliable performance across various operating conditions. The interplay between the tangential magnetic field and temporal periodicity generates additional mechanisms of mode coupling and amplifies instability. These observations address critical shortcomings in nonlinear stability theory and suggest practical uses in flow regulation and the control of conductive fluids. The fluids are assumed as Eyring–Powell non-Newtonian and flow with uniform velocities through porous media. The analysis is conducted using a non-perturbative method that relies mainly on He’s frequency formulation. To facilitate the mathematical treatment, viscous potential theory is adopted. The governing linear partial differential equations describing the flow are then solved under nonlinear boundary conditions, resulting in a nonlinear characteristic equation that represents the displacement of the interface. A non-dimensional procedure is then applied to extract the key dimensionless physical parameters influencing the system behavior. A set of graphical results is provided to demonstrate how the system’s stability behavior is influenced by changes in the key dimensionless physical parameters. The validation of the innovative process is achieved using Mathematica Software. The study considers both uniform and periodically varying magnetic fields, and the associated stability conditions are evaluated for each case, where the impacts of various non-dimensional attributes are assessed. As density ratio increases, it stabilizes periodic magnetic fields while destabilizing uniform ones. A stronger MF enhances magnetic damping, reducing instability regions and promoting stable periodic interfacial motion. Enhanced conductivity improves Magnetohydrodynamic interactions, resulting in greater energy dissipation and stability. Full article

This article presents a comprehensive analytical, numerical, and experimental study of the amplification and detection of weak signals in magnetically coupled electromagnetic systems, using an architecture consisting of three magnetically coupled coils. A rigorous mathematical model of the system is developed, which includes the formulation of the mutual inductance matrix and a state-space representation that captures the dynamic interaction between the coils. It is important to note that the electromagnetic subsystem is linear and that the stochastic resonance effect is achieved by incorporating an external nonlinear bistable element. In this configuration, a weak periodic signal below a threshold is applied to the primary coil, while a controlled source of Gaussian white noise is injected into a secondary coil. A third coil functions as a sensing element, capturing the superimposed magnetic response resulting from coupling effects. The voltage induced in the sensor coil is subsequently processed by a bistable nonlinear element implemented via a Schmitt trigger, which provides the nonlinearity and bistability necessary to enable stochastic resonance and the detection of the weak periodic signal. The conditions of the SR are analyzed in terms of noise intensity, coupling coefficients, and system parameters, highlighting the existence of an optimal noise level that maximizes the signal-to-noise ratio (SNR) at the output. A detailed simulation framework has been developed in MATLAB/Simulink, enabling a systematic exploration of the parameter space and the validation of theoretical predictions. The simulation results are further supported by experimental measurements obtained from a physical prototype, which show agreement with the proposed model. The main contribution of this work lies in demonstrating that magnetically coupled electromagnetic structures can effectively interact with nonlinear bistable elements to exploit stochastic resonance in the detection of weak signals, even when the electromagnetic domain itself remains linear. The results demonstrate that magnetic coupling is an effective mechanism for mediating constructive interactions between noise and weak signals, thereby improving the detection of the latter. These results extend the applicability of stochastic resonance to hybrid electromagnetic systems and demonstrate its relevance in practical applications. Potential applications include ultra-sensitive magnetic detection, low-power signal detection, magnetic transducers, and robust signal recovery in noisy electromagnetic environments, particularly in contexts where conventional linear amplification fails. Full article

Multifunctional polymer–ferrite composites based on poly(vinylidene fluoride) (PVDF) and magnetic fillers are of increasing interest for applications requiring coupled electrical, dielectric, and magnetic responses. However, the relationship between magnetic filler concentration, PVDF phase composition, and the resulting multifunctional properties remains insufficiently understood. In this work, PVDF/BaFe₁₂O₁₉ (PVDF/BaF) composite membranes containing 2–20 wt.% BaF were fabricated using a combined non-solvent and thermally induced phase-inversion (NIPS–TIPS) method. Structural evolution was analyzed by X-ray diffraction and quantitative FTIR spectroscopy, thermal behavior by differential scanning calorimetry, optical properties by diffuse reflectance spectroscopy, dielectric response in the frequency range 10³–10⁶ Hz, and magnetic characteristics by vibrating sample magnetometry. At moderate filler concentrations (2–10 wt.%), BaFe₁₂O₁₉ nanoparticles acted as effective β-phase nucleating centers, leading to electroactive phase fractions of 97.7–99.9% and a maximum β-phase content of 86.7% for PVDF/BaF10. At higher loadings (15–20 wt.%), particle agglomeration and restricted chain mobility promoted a transition toward α-phase-dominated crystallization. Thermal analysis indicated competing nucleation and confined crystallization processes, while optical and dielectric measurements revealed nonmonotonic changes associated with interfacial interactions and Maxwell–Wagner–Sillars polarization. Magnetic measurements showed a linear increase in saturation magnetization with filler concentration and a nonmonotonic coercivity dependence with a pronounced change near the critical agglomeration concentration. These results demonstrate that the multifunctional response of PVDF/BaFe₁₂O₁₉ membranes is governed by the interplay between β-phase nucleation, interfacial polarization, and magnetic particle interactions, with approximately 10 wt.% ferrite providing the most balanced electrical, dielectric, and magnetic characteristics. Full article

This paper presents a real-time magnetic adhesion force estimation framework for wall-climbing robots equipped with Halbach permanent magnet arrays (PMAs) and air-gap–adjustable mechanisms. Accurately computing the magnetic adhesion force between a PMA and a large ferromagnetic surface is challenging due to the nonlinear magnetization behavior of soft magnetic materials and the strongly coupled, highly nonuniform magnetic fields generated by Halbach arrays. Conventional analytical models fail to capture these effects, while finite element methods (FEM) incur prohibitive computational cost for real-time applications. To address this, we propose an analytical magnetic-force estimation model based on the magnetostatic MoI (Method of Images), which replaces the unknown magnetization inside the steel plate with an equivalent image magnet distribution that satisfies boundary conditions at the air–steel interface. The method avoids solving complex magnetization in soft magnetic media and enables a unified force computation for arbitrarily oriented magnet elements. Additionally, complex Halbach PMA geometries are approximated through cuboid-element segmentation into cuboid magnet array, allowing efficient force evaluation. Comparative studies demonstrate that the proposed method achieves accuracy comparable to FEM while reducing computation time by several orders of magnitude. Experimental validation using a linear Halbach array and a large steel plate proved that the framework can reliably estimate magnetic adhesion force across varying air-gap distances, meeting the real-time requirements of air-gap–adjustable wall-climbing robots. Full article

In this article, a compact wideband three-slot filtering antenna is proposed. The antenna consists of a U-shaped driven slot, a folded resonant slot, and a linear resonant slot. A microstrip feedline with a shorting via is employed to excite the antenna. Mixed electric and magnetic couplings enable the driven slot to couple to the two resonant slots. Three resonant frequencies lie within the passband, resulting in wideband operation. The lowest resonant frequency is determined by the folded resonant slot, while the highest resonant frequency is determined by the linear resonant slot. The center resonant frequency is influenced by the combined effects of the U-shaped driven slot, the folded resonant slot, and the linear resonant slot. A low-frequency radiation null at 1.68 GHz and a high-frequency radiation null at 3.19 GHz are generated. These two radiation nulls enable the proposed antenna to achieve excellent filtering performance. A prototype was fabricated and measured. The measured results are in good agreement with the simulated ones. The measurements show that the proposed three-slot filtering antenna exhibits a relative impedance bandwidth of 39.1%. The out-of-band suppression levels reach 12.5 dB and 14.8 dB in the lower and upper sidebands, respectively. The proposed three-slot filtering antenna is suitable for applications in wireless communication systems. Full article

To address the issues of poor control performance, synchronization defects, and instability in existing multi-pole permanent magnet synchronous motor (PMSM) control systems using PI control, this paper proposes an optimized control strategy combining Linear Active Disturbance Rejection Control (LADRC) with Capuchin Search Algorithm (CapSA). The proposed approach first implements LADRC in the PMSM speed loop, where the CapSA algorithm is applied to tune LADRC parameters, significantly reducing overshoot, enhancing the disturbance rejection capability, and improving the system stability. Secondly, by modifying the traditional deviation coupling structure and introducing an error factor to strengthen dynamic synchronization performance among multiple motors, the system’s control accuracy and robustness are effectively enhanced. Finally, a simulation model is established using MATLAB/Simulink for comparative experiments under various operating conditions. The results demonstrate that the proposed CapSA-LADRC control strategy significantly reduces speed overshoot and synchronization errors while exhibiting superior dynamic response and disturbance rejection capabilities, providing a reliable solution for practical engineering applications. Full article

To address the insufficient accuracy of conventional permanent magnet synchronous motor (PMSM) models caused by neglecting magnetic saturation nonlinearity and periodic parameter disturbances, a nonlinear motor system model integrating a Physics-Informed Neural Network (PINN) is developed. By exploiting the differential relationships among incremental inductance, flux linkage, and magnetic energy, the voltage and torque equations considering rotor position variation are derived, and analytical expressions for the derivatives of incremental inductances are obtained. To reduce the computational burden of PINN in system-level simulations, linear and nonlinear approximation strategies based on incremental inductances and their derivatives are proposed, which significantly reduce the frequency of PINN calls while maintaining model accuracy. CPU/GPU collaborative computation and cross-frequency-domain scheduling are further implemented to improve simulation efficiency. Considering the influence of the test bench mechanical dynamics, an electromechanical–magnetic coupled simulation model is established. The accuracy of the proposed nonlinear motor model is validated through two-phase short-circuit tests as well as simulations and test bench experiments under sinusoidal and non-sinusoidal excitations. The results demonstrate that the proposed model accurately captures the nonlinear electromagnetic characteristics of PMSMs while significantly improving system simulation efficiency. Full article

This paper presents a novel dual-module Permanent Magnet Linear Synchronous Motor (PMLSM) featuring an unequal tooth-shoe topology, alongside a highly efficient surrogate-assisted framework to maximize average thrust and minimize thrust ripple. To overcome the computational bottleneck of expensive Finite Element Analysis (FEA), we propose a Constraint-Preserving Maximin Latin Hypercube Design (CP-MmLHD) coupled with an ARD-Kriging model and the Expected Hypervolume Improvement (EHVI) criterion. This closed-loop framework expertly handles strict geometric constraints and anisotropic parameter sensitivities. Within a strict budget of only 150 FEA evaluations, the framework successfully identifies a high-quality Pareto front. Notably, a representative optimal design reduces thrust ripple by over 80% without compromising average thrust. Furthermore, comparative experiments demonstrate superior computational efficiency over conventional algorithms, while multi-run statistical benchmarking and stochastic Monte Carlo analysis rigorously confirm the framework’s algorithmic robustness and manufacturing reliability. Full article

This study introduces a modified computational scheme for handling linear and nonlinear fractal time-dependent partial differential equations. The method is constructed using three different stages that provide third-order accuracy in the fractal time variable. The stability of the approach is examined using scalar fractal models and Fourier analysis, while convergence is established for coupled convection–diffusion systems. The numerical algorithm is applied to analyze the mixed convective flow of a Carreau–Yasuda non-Newtonian fluid over stationary and oscillating plates under the influence of viscous dissipation and magnetic field effects. For spatial discretization, the incompressible continuity equation is handled by a first-order difference scheme, whereas higher-order compact schemes are implemented for the momentum, thermal, and concentration equations. The numerical findings show that increasing the Weissenberg number and magnetic field inclination reduces the velocity distribution. An accuracy assessment against existing numerical techniques demonstrates that the present method yields smaller computational errors, particularly when central difference schemes are used in space. In addition, a surrogate machine learning model is developed to predict the skin friction coefficient and local Nusselt number using Reynolds, Weissenberg, Prandtl, and Eckert numbers as input features. The predictive capability of the model is validated through Parity plots, bar charts for sensitivity analysis, scatter visualization, and Taylor Diagrams, confirming strong agreement with the numerical results. Full article

Floating roof seal integrity is critical for safety and emission control in petroleum storage tanks, yet current detection methods suffer from spark risks and operational inefficiencies. This study proposes an intrinsically safe, non-contact leakage detection system utilizing oil-swellable rubber actuators coupled with a linear magnetic transmission mechanism. By integrating quasi-static experiments with finite element simulations, we investigated the impact of permanent magnet geometry on transmission performance. The results establish a “thickness priority principle”, revealing that increasing magnet thickness nonlinearly enhances shear force and transmission efficiency, whereas increasing width yields diminishing returns due to magnetic flux leakage and added mass. Furthermore, comparative analysis demonstrates that optimized monolithic magnets significantly outperform arrayed configurations, achieving a 471% increase in shear force and a 3.7-fold improvement in transmission efficiency. Based on these findings, a practical detection device was designed and verified against API 650 standards. The proposed solution offers a reliable, electricity-free, and real-time monitoring method for early leakage detection in hazardous tank environments. Full article

In this work, a comprehensive first-principles investigation of the electronic, magnetic, and optical properties of pristine and Fe-, Co-, and Ni-doped MoS₂ monolayers is presented within the framework of density functional theory. Substitutional transition-metal doping at the Mo site is shown to induce spin-polarized impurity states within the pristine band gap, leading to significant modifications of the electronic structure, including metallic, semimetallic, or half-metallic behavior depending on the dopant species. The calculated spin-resolved band structures and projected density of states reveal a strong hybridization between the dopant $3d$ orbitals and the Mo-$4d$/S-$3p$ states, giving rise to sizable magnetic moments and dopant-dependent exchange splitting. When spin–orbit coupling is included, the combined effect of exchange interactions and relativistic effects leads to an effective valley splitting at the K and $K^{\prime }$ points, whose magnitude and sign depend sensitively on the chemical nature of the dopant. Optical properties are analyzed within a linear-response framework, showing pronounced dopant-induced modifications of the optical spectra. While the pristine monolayer exhibits well-defined excitonic features, transition-metal substitution introduces low-energy optical transitions associated with impurity-related states. Consequently, the exciton binding energies estimated from the difference between the electronic and optical gaps are interpreted as effective measures of dopant-induced perturbations to optical transitions, rather than as quantitative many-body excitonic binding energies in the strict sense. These results provide microscopic insight into the interplay between magnetism, spin–orbit coupling, and optical response in doped MoS₂ monolayers, highlighting the potential of transition-metal substitution as a route to engineer spin- and valley-dependent phenomena in two-dimensional materials. Full article

Fluoroquinolones (FQs) are a kind of antibiotics, which are widely used in animal husbandry and aquaculture. However, the abuse of FQs can result in residues in foodstuffs of animal origin. Therefore, it is essential to establish a sensitive and accurate detection method for determination of FQs in food samples. An effective sample pretreatment method is a crucial procedure for enrichment of trace target compounds from complex matrix before HPLC analysis. As an emerging kind of sample pretreatment methods, magnetic solid-phase extraction (MSPE) has attracted much interest due to its characteristics including low cost, simplicity, and rapidity. In this study, a novel fluorinated magnetic covalent organic framework (Fe₃O₄@PDA@COF) was fabricated, which was used as an adsorbent in MSPE as well as coupled with HPLC to determine FQs in food samples. Under optimal conditions, the developed Fe₃O₄@PDA@COF-MSPE-HPLC-UV method possessed a wide linear range (1–250 µg·kg⁻¹) and low limits of detection (0.5–0.7 µg·kg⁻¹) with good linearity (R² ≥ 0.9938). Additionally, the method has been used to adsorb FQs from chicken samples. The recoveries of target FQs in spiked samples were 84.2–106.7% with relative standard deviations (RSDs) below 7.8%. These results demonstrated that the established method provides an efficient and sensitive solution for monitoring FQ residues in foodstuffs. Full article

To minimize the construction cost of track beam and enhance the dynamic performance of the magnetic suspension system, a simplified coupled vibration model of the electromagnet-track beam-vehicle body was established. Initially, by defining a Lyapunov function to represent the quadratic performance index of the maglev system under parameter perturbation, the controller design problem for the closed-loop system was transformed into an existence problem of linear matrix inequality (LMI) solutions. Consequently, a state-feedback cost-preserving robust controller for a flexible track beam was designed. Subsequently, the impact of the suspension controller on the dynamic characteristics of the flexible track beam, both with and without considering parameter perturbation, was compared and analyzed. Furthermore, the robustness, high-frequency suppression, and low-frequency following characteristics of the LMI-based controller were evaluated. Finally, the influence of two distinct state feedback controllers on the dynamic characteristics of the flexible track beam across different frequency bands was analyzed. Correlation analysis revealed that accounting for parameter perturbation can improve the suspension and dynamic characteristics of the suspension controller. When the system experiences parameter perturbation, the LMI-based suspension controller can achieve stable suspension on the flexible track beam while demonstrating strong robustness, high-frequency suppression, and low-frequency following capabilities. On the flexible beam, controllers with different state feedback exhibit varying dynamic characteristics in different vibration frequency segments of the track beam. Specifically, reducing the feedback state variables in the low-frequency band and increasing them in the high-frequency band can appropriately improve the system’s dynamic characteristics. Full article

In the single-winding consequent-pole bearingless permanent magnet synchronous motor (SW-CP-BPMSM), the torque and suspension systems utilize a shared winding configuration. This structure significantly intensifies inter-system coupling. Furthermore, the presence of non-linear and strongly coupled relationships among structural parameters, combined with inherent coupling and conflicts between optimization objectives, makes the unified optimization of key performance indicators for both the torque and suspension systems a substantial challenge. To address these issues, this paper proposes a dual-system interactive optimization strategy based on the classification of sensitive variables. First, the strategy employs the Sobol method to conduct a global sensitivity analysis. By defining dual-system coupled sensitive parameters and single-system sensitive parameters, the method achieves dimensionality reduction through parameter classification. Subsequently, Response Surface Methodology (RSM) and Back Propagation (BP) neural network surrogate models are constructed for the suspension and torque systems, respectively. A progressive optimization process—comprising single-system optimization followed by dual-system interactive optimization—is then performed on the single-system and dual-system sensitive variables to determine the final optimal parameters. Finally, a comparative simulation analysis of the key performance indicators for both the torque and suspension systems before and after optimization is conducted. The results validate the feasibility and effectiveness of the proposed optimization strategy. Full article