A rapid method that uses super-resolution magnetic array data is proposed to localize an unknown number of magnets in a magnetic array. A magnetic data super-resolution (SR) neural network was developed to improve the resolution of a magnetic sensor array. The approximate 3D positions of multiple targets were then obtained based on the normalized source strength (NSS) and magnetic gradient tensor (MGT) inversion. Finally, refined inversion of the position and magnetic moment was performed using a trust region reflective algorithm (TRR). The effectiveness of the proposed method was examined using experimental field data collected from a magnetic sensor array. The experimental results showed that all the targets were successfully captured in multiple trials with three to five targets with an average positioning error of less than 3 mm and an average time of less than 300 ms.

Recently, magnetoelectric (ME) antennas have become a hot topic in the field of antenna miniaturization in the very-low-frequency (VLF) band because their size can be reduced to one-ten-thousandth of the size of conventional electric antennas. However, they still suffer from narrow transmission/reception bandwidth and weak radiation intensity. To address these issues, VLF thin-film ME antennas with a microbridge structure are designed, and the method of array connection is used. Test results show that the detection limit of the ME antenna unit is 636 pT/√Hz at 23 kHz and the radiant magnetic field intensity at 0.12 m is 0.87 nT (input power of 10 mW). By series-connecting three ME antenna units with the same resonance frequency, the output response has been increased to 1.72 times and the EM wave radiation intensity is increased to 1.9 times compared to a single unit. By parallel-connecting two ME antenna units with different resonance frequencies, the output response bandwidth has been expanded to 1.56 times compared to a single unit, and the signal radiation bandwidth has been expanded to 1.47 times. This work provides a valuable reference for the future larger-scale arraying of ME antennas.

The degaussing process is crucial for ensuring magnetic protection in ships. It involves the application of oscillating and attenuating magnetic fields to eliminate residual magnetism in the ship’s structure. However, this process can lead to the generation of distorted magnetic fields within the ship’s cabin, posing a potential threat to electronic equipment performance. Therefore, it is essential to have a comprehensive understanding of the dynamic magnetic field response in ship structures to develop effective degaussing systems. To address this need, this paper proposes an eddy current model for analyzing the dynamic magnetic field response in ferromagnetic metal structures. This model focuses on the role of eddy currents in shaping the magnetic field response and provides valuable insights into the underlying mechanisms. Using the proposed eddy current model, the effects of key system parameters such as thickness, conductivity, and the length-scale of the ship structure can be analytically investigated. This analysis helps in understanding how these parameters influence the dynamic magnetic field response and aids in the design and optimization of degaussing systems. The effectiveness and applicability of the proposed eddy current model are demonstrated through comprehensive investigations involving two simulation cases of varying complexity. The model accurately predicts the changing trends of the dynamic magnetic field response, as confirmed through finite element simulations. This validation highlights the model’s ability to reproduce simulation results accurately and its potential as a powerful tool for analyzing and optimizing dynamic magnetic field responses. In summary, the proposed eddy current model represents a significant advancement in the field. It provides a valuable theoretical framework for understanding and analyzing the dynamic magnetic field response in ferromagnetic metal structures. By offering insights into the underlying mechanisms and the influence of key parameters, this research contributes to the development of improved degaussing systems and enhances the overall magnetic protection capabilities of ships.

The initial workpiece diameter is one of the most fundamental process parameters in sheet metal forming, as it determines the resistance of the draw-in material flow. In the context of conventional deep drawing, its critical role has been clearly identified. In the context of electromagnetic sheet forming, however, its role has not yet been adequately addressed. This paper aims to clarify its role, by experimentally and numerically investigating the deformation behavior of circular sheet metal in electromagnetic forming. Various combinations of the initial diameter and discharge voltage were established to induce different deformation behaviors. It was found that adjusting the initial diameter can substantially change the forming height, shape, and thickness distribution by altering the draw-in, which suggests a great improvement in deformation controllability. In summary, this study demonstrates that the initial workpiece diameter could play critical role in deformation control in electromagnetic forming.

To address the issues of low signal-to-noise ratios in detecting weak shaft-rate magnetic fields of underwater targets in complex marine environments, the poor identification capability of traditional detection methods, and difficulty in recognizing unknown frequency signals, this study proposes a differential high-order dual-coupled Duffing oscillator detection method. A dual-oscillator model containing a cubic coupling term was constructed, and common-mode interference was suppressed through a differential structure. Simultaneously, a scale-dispersion joint statistical feature quantity was designed to automatically determine the critical threshold of system phase transition. Combined with refined composite multiscale dispersion entropy to quantitatively determine intermittent chaotic states, the method enabled the detection of weak shaft-rate magnetic fields with unknown frequencies and high-precision frequency estimation. Both simulation and marine experimental results demonstrate that compared with traditional Duffing oscillator detection methods, this approach significantly improved detection accuracy and reduced false alarm rates, making it applicable to underwater target monitoring, port security, and related scenarios.