Search Results (2,367)

This paper proposes a generalized high-order linear active disturbance rejection control (GHO-LADRC) method to suppress non-stationary disturbances in VICTS antenna direct-drive motors during high-dynamic scanning. First, a fourth-order generalized extended state observer is constructed, in which the derivative of the total disturbance is explicitly modeled as an extended state. This configuration enables real-time observation of the disturbance rate of change and suppresses the phase lag inherent in traditional ADRC during rapid disturbance variations through disturbance feedforward compensation. Secondly, drawing on singular perturbation theory and the motor’s dual-time-scale characteristics, this work precisely decouples and explicitly extracts the nonlinear friction and electromagnetic damping terms during the modeling stage. By integrating the extracted electromagnetic damping terms and the disturbance variation rate, an improved model-assisted control law is formulated, enabling active compensation for intense dynamic interference. Theoretical analysis and experimental results demonstrate that the proposed method significantly enhances disturbance rejection capability and satellite communication accuracy. As the first application of GHO-LADRC in the field of direct-drive VICTS antenna control, this work validates its effectiveness in improving system robustness within complex dynamic environments. Full article

This paper proposes a novel arch-shaped-magnet variable-flux memory machine (ASM-VFMM). The proposed machine adopts a dual-layer permanent magnet (PM) rotor structure. In the first layer, an arch-shaped magnet arrangement is utilized to increase the volume of low-coercive-force (LCF) magnets, which contributes to improved magnetic flux adjustment (MFA) performance. The second layer incorporates an asymmetric PM (APM) layout to create a parallel magnetic circuit, enabling further suppression of air-gap flux density at the weakened-flux state. The topological development of the proposed machine is first described, covering the conventional series magnetic circuit (SMC) structure, the intermediary APM structure, and the proposed ASM structure. A theoretical modeling analysis is then conducted for the three machines. This confirms the superiority of the proposed design regarding its MFA capability. A comprehensive electromagnetic performance evaluation is carried out for the proposed machine, alongside comparative assessments of the other two machines. The results show that the proposed design outperforms the other two machines in terms of magnetization performance, MFA range, and on-load magnetization stabilization capability. Notably, the proposed machine exhibits excellent overall efficiency characteristics, especially under high-speed operating conditions. Full article

Ground penetrating radar (GPR), as an efficient non-destructive testing technique, plays a crucial role in the structural condition assessment and defect identification of railway ballast. Typical defects such as mud pumping generally exhibit characteristics in B-scan images including weak reflections, blurred boundaries, and irregular structures, which pose significant challenges for stable detection and precise localization using existing methods that rely primarily on spatial feature modeling. Most current deep learning approaches focus on modeling spatial or temporal information, while lacking effective utilization of frequency-domain features, thereby limiting their discriminative capability under complex electromagnetic environments. To address these issues, this paper proposes a single-stage object detection framework, termed YOLO-DGW, based on time-frequency collaborative modeling. Built upon YOLOv8, the proposed method introduces a structure-aware spatial enhancement module to improve the representation of continuous GPR echo structures. Meanwhile, frequency-domain information is incorporated as a modulation prior to guide spatial feature learning, enhancing the model’s sensitivity to weak reflections and complex-shaped targets. In addition, A-CIoU loss function is designed to improve localization accuracy and stability for defect regions of varying scales. Experimental results demonstrate that YOLO-DGW achieves an F1-score of 63.06% and an AP@0.50 of 62.07%, representing improvements of approximately 7.41% and 2.8%, respectively, over the strongest baseline method. Compared with several mainstream object detection models, the proposed approach exhibits superior performance in both detection accuracy and cross-region generalization capability. These findings indicate that integrating frequency-domain information into spatial feature learning through a modulation mechanism can effectively enhance the model’s ability to discriminate weak-reflection anomalies, providing a novel time-frequency collaborative modeling paradigm for railway GPR defect detection. Full article

Non-Line-Of-Sight (NLOS) Terahertz (THz) radar 3D imaging leverages electromagnetic wave propagation characteristics such as reflection, diffraction, scattering, and penetration to detect, locate, and image hidden targets in occluded environments. It holds significant potential for applications in autonomous driving, disaster rescue, and urban warfare. However, uncertainties introduced by reflecting surfaces and occluding objects in practical NLOS scenarios, such as phase errors, aperture shadowing, and multipath effects, lead to issues like blurred imaging and increased artifacts in radar imaging. To address these challenges, this study proposes a 3D learning imaging method for NLOS THz radar based on a holographic imaging operator, leveraging the adaptive optimization properties of deep unfolding networks and prior environmental perception. First, a 3D imaging model for NLOS THz radar in the Looking Around Corner (LAC) scenario is established. A holographic imaging operator is introduced to enhance imaging efficiency and reduce computational complexity. Second, a high-precision NLOS 3D imaging network is constructed based on the Fast Iterative Shrinkage/Thresholding Algorithm (FISTA) framework. Utilizing features specific to NLOS scenes and designing algorithm parameters as functions of network weights, the method achieves high-precision and high-efficiency in the 3D reconstruction of NLOS targets. Finally, a near-field NLOS radar imaging platform operating at 121 GHz (within the sub-THz regime) is developed. Experimental validations in the LAC scenario are performed on targets, including metal letters “E”, a metal resolution chart, and a pair of scissors. The results demonstrate that the proposed method significantly improves 3D imaging precision, achieving a two-orders-of-magnitude increase in computational speed over traditional imaging algorithms. Full article

The purpose of this research is to determine which factors contribute to extending the read range of transponders equipped with different coupling-circuit topologies operating within selected RFID frequency bands. The analysis covered transponders that varied in both the configuration of their coupling circuits and their geometric dimensions. To accomplish this, transponder models were created using the EMCoS Studio electromagnetic simulation environment. Each model was subjected to simulations that yielded the mutual inductance and the voltage induced at the chip terminals. This study examines how the impedance of the embroidered antenna, the impedance of the chip’s coupling circuit, and the magnetic flux density affect the resulting chip voltage. In several of the investigated configurations, the peak chip voltage appeared outside the frequency range normally associated with RFID systems. The frequency at which this maximum occurred was dependent on the mutual inductance value. Understanding how individual parameters influence mutual inductance makes it possible to shift the voltage peak into a target operating band. Numerical simulation results, combined with the transponder’s mathematical model, enabled the calculation of the mutual inductance and the terminal voltage—quantities that directly determine the achievable read range. This study focuses on factors such as the resonant frequencies of the antenna and coupling circuit, their impedances, and the characteristics of the magnetic field. The findings show that tuning these parameters can affect not only the location of the voltage maximum, but also its amplitude. This effect introduces additional complexity in designing and selecting suitable transponder configurations. Full article

To address the issue of traditional bistable vibration energy harvesters (BVEHs) being prone to becoming trapped in a single potential well—which results in a narrowed energy harvesting bandwidth and reduced efficiency—this paper proposes a method that utilizes the nonlinear electromagnetic force generated during the induction process to modulate the kinematic behavior of the oscillator. The characteristics and influencing factors of the nonlinear force produced during electromagnetic induction are analyzed. A dual-cantilever beam structure is designed, with an iron-core coil and a magnet placed at the respective free ends. A mathematical model of a piezoelectric–electromagnetic coupled bimodal broadband vibration energy harvester is established and numerically simulated. Furthermore, a vertical vibration experimental platform is constructed to conduct frequency sweep tests. The experimental results demonstrate that the proposed piezoelectric–electromagnetic coupled bimodal broadband vibration energy harvester effectively improves energy harvesting efficiency. Within the frequency range of 5–20 Hz, the system exhibits two vibration modes, with resonant frequencies of approximately 7.7 Hz and 15.7 Hz. For a single-layer PVDF piezoelectric film, the maximum output power at the first and second resonance points is 8.9 μW and 9.7 μW, respectively. The electromagnetic module achieves maximum output powers of 0.39 W and 0.71 W. Moreover, within the frequency ranges of 6.3–9.8 Hz and 14–17.7 Hz (a total bandwidth of 7.2 Hz), the device maintains a stable power output. The effective bandwidth is broadened by approximately 80%, demonstrating excellent broadband performance. Full article

Vibration energy is widely present in the natural environment. In the development of wearable self-powered systems, how to efficiently harvest the low-frequency mechanical energy of human motion has always been a core challenge. The piezoelectric–electromagnetic hybrid energy harvester designed in this paper consists of two units: a piezoelectric unit and an electromagnetic unit. The piezoelectric unit is composed of two arched plates, a piezoelectric layer, and an end magnet. The two sides of the piezoelectric unit are completely symmetrical. The electromagnetic unit is composed of a hollow tube, a central magnet, and a coil. The coil is wound around the outside of the center of the hollow tube to ensure that the central magnet can cut more magnetic flux lines. The two units output voltage through an external load. Firstly, based on a physical model, the force–electricity coupling mechanism is derived, and the dynamic response of the harvester at different frequencies is systematically tested. Secondly, through simulation and experiment, the influencing factors of the output voltage are deeply studied, and it is concluded that at medium and low frequencies (5 Hz–15 Hz), the harvester can provide efficient voltage output. The electromagnetic unit dominates at low frequencies and can output a larger voltage, but the voltage drops significantly after a certain frequency. The piezoelectric unit can supplement after the electromagnetic voltage drops, and the two have a synergistic effect. In addition, the output characteristics of the system mainly depend on frequency, initial distance, coil turns, and magnet mass. This paper clarifies the inherent physical mechanism of the hybrid energy harvester and provides an effective scientific reference for practical human motion energy conversion applications. Full article

Accurate measurement of spool displacement is essential for achieving high-performance closed-loop control and condition monitoring in hydraulic systems. However, conventional inductive displacement transducers typically rely on sinusoidal excitation and complex analog signal conditioning circuits, resulting in higher hardware cost and limited system integration. To address these issues, this paper proposes a software-based demodulation method for a differential inductive displacement transducer under symmetric complementary square-wave excitation. First, the structure and operating principle of the transducer are analyzed, and an electromagnetic model describing the nonlinear relationship between coil inductance and the position of the inductive core is established, along with its electrical characteristics. Then, a simplified signal acquisition circuit is designed to enable digital extraction of inductance variations using a microprocessor. Compared with conventional approaches, the proposed scheme significantly reduces hardware complexity and cost while being more suitable for embedded system integration. A simulation model is developed to analyze the inductance variation and to validate the proposed hardware circuit. In addition, a test platform is built to conduct static calibration and dynamic response experiments. The experimental results show that the proposed method achieves a linearity of 2.36% and a sensitivity of 155.6 mV/mm and exhibits strong robustness against switching noise. Finally, application tests in a hydraulic valve system demonstrate that the proposed transducer and demodulation method enable accurate and stable spool position measurement, providing a low-cost and easily integrated solution for embedded hydraulic control systems. Full article

Chalcogenide glasses are known as optical materials for the infrared spectral range. These compounds may also be of interest as materials for the low-frequency part of the terahertz range of electromagnetic waves, which is currently being intensively studied in connection with the numerous possible applications of terahertz radiation. However, the terahertz optical characteristics of chalcogenide glasses remain poorly studied. In this work, eight different compositions of GeAsSeSbSnTe chalcogenide glasses were investigated using terahertz time-domain spectroscopy. A number of compositions, in particular GeSeTe and AsSeSbSn, were studied in the terahertz spectral range for the first time. Spectra of the refractive index and extinction coefficient were obtained for studied materials in the spectral range of 0.1–2.2 THz. The experimental frequency dependence of the product of the terahertz power absorption coefficient and the refractive index for the entire set of studied glasses is approximated by a power function. It was established that the exponent of the approximating power functions varies from 1.68 to 2.34 depending on the composition of the chalcogenide glass. For the studied glasses, a correlation was found between the values of the average coordination number characterizing the chalcogenide glass structure, and the values of the exponent of the functions approximating the THz absorption spectra. Full article

This article concerns the issue of contactless estimation of the complex electrical permittivity of masonry materials by means of a microwave technique in the frequency domain. The main aim of the study was to develop a method enabling the determination of the real part of relative permittivity and the electrical conductivity of ceramic building materials using microwave reflection measurements, as well as to assess the applicability of the proposed approach for moisture diagnostics in porous media. The research was performed using a reflection-mode measuring setup comprising a vector network analyser and a broadband horn antenna, while measurements were carried out in the frequency range from 1 to 6 GHz on samples of solid ceramic brick with six gravimetric moisture levels. A one-dimensional model of electromagnetic wave propagation in the material was developed, considering complex permittivity, impedance transformation, and a calibration procedure compensating for the influence of the antenna and free-space propagation. Based on the fitting of the magnitude and phase characteristics of the reflection coefficient, the electrical parameters of the tested samples were estimated. The results obtained showed an increase in both permittivity and conductivity with increasing moisture content and revealed very good agreement with the reference values determined using the time-domain method. It can be concluded that the frequency-domain microwave approach may be effectively applied for contactless and non-destructive diagnostics and estimation of the dielectric properties and moisture content in ceramic materials. Full article

With advancements in weak magnetic detection technology, the electromagnetic wake signals induced by UUVs in stratified seawater are becoming stable interference sources for detection equipment. This study developed a numerical model combining fluid dynamics and electromagnetism to examine the electromagnetic wake evolution of the UUV system under varying propeller propulsion coefficients, and formation mechanism of the wake electromagnetic field is revealed. The flow field results were validated using PIV and relevant literature. The flow characteristics of the near-field wake are analyzed by visualizing the vortex structure. Additionally, this study investigates the attenuation law of far-field wake using electromagnetic field intensity attenuation curves. The wake’s electromagnetic field frequency characteristics were examined through the normalized amplitude spectrum. Results indicate that the near-field wake vortex structure resembles a propeller’s topological structure. The electric field intensities in the near-field and far-field are approximately on the order of 10⁻⁴ V/m and 10⁻⁵ V/m, respectively, while the magnetic field intensities are around 10⁻¹⁰ V/m and 10⁻¹¹ V/m. The electromagnetic interference spectrum within the wake typically shows high intensity in the low-frequency band. A high-precision magnetometer can detect the electromagnetic field’s intensity and frequency characteristics. It offers theoretical support for developing advanced anti-interference algorithms in engineering practice. Full article

The rapid expansion of wireless communication in urban environments requires antenna systems that balance high electromagnetic performance with stringent aesthetic and security constraints. This review examines recent advances in concealed antenna technologies integrated into building structures, with a focus on performance variation, material-induced attenuation, and emerging concealment strategies. Techniques such as transparent conductors on glass, structural embedding within walls, and camouflage-based designs are shown to significantly influence resonance behavior, radiation efficiency, and pattern characteristics compared to free-space operation. Despite these challenges, optimized solutions including transparent conductive oxide arrays, wideband embedded antenna geometries, and metasurface-enhanced window structures can partially recover performance while maintaining optical transparency above 70%. Material loading effects are found to induce resonant frequency shifts of approximately 10–44%, depending on dielectric properties and environmental conditions. Transparent antenna arrays achieve gains ranging from 0.34 to 13.2 dBi, while signal-transmissive wall systems demonstrate transmission improvements of up to 22 dB relative to untreated building materials. These technologies enable a wide range of applications, including 5G and beyond-5G cellular networks across sub-6 GHz and millimeter-wave bands, as well as Internet of Things systems and smart city infrastructure. However, key challenges remain, including the need for comprehensive characterization of building material electromagnetic properties, optimization of multilayer structural environments, and the development of standardized design and evaluation methodologies. This review provides a unified framework for understanding the tradeoffs associated with antenna concealment and identifies critical research directions for the development of building-integrated wireless systems in next-generation communication networks. Full article

The increasing integration of nonlinear loads in modern power systems has made harmonic pollution a critical challenge to the operational safety of power cables. This study develops a frequency-dependent high-voltage cable system model using the ATP-EMTP (Alternative Transients Program-Electro Magnetic Transient Program) electromagnetic transient simulation platform, systematically investigating the amplification mechanisms and propagation characteristics of grounding currents under multi-type harmonic disturbances. A frequency-dependent parameter correction model is established by integrating the conductor skin effect and the dielectric relaxation properties of the insulation layers. This model incorporates the multi-structure combination among conductors, insulation, and metallic screen. It effectively overcomes the limitations of conventional lumped-parameter models in higher frequency harmonic analysis. Key findings are as follows: (1) The combined influence of harmonic frequency and amplitude leads to a grounding current amplification of up to 445 times (at 1950 Hz with 30% distortion level). Notably, current-source excitation produces significantly greater amplification than voltage-source excitation. (2) The distributed capacitance of long-distance cables (>8 km) exacerbates resonance risks within specific frequency bands (750–1250 Hz), resulting in a maximum harmonic amplification factor of 34.73 (observed for the 17th harmonic in a 15 km cable). (3) The contribution of voltage-source harmonics diminishes to less than 5% of the total current at high frequencies (≥1250 Hz), indicating a pattern of current-dominated harmonic superposition. Full article

Structural health monitoring (SHM) plays an increasingly important role in managing aging, safety-critical infrastructure under growing environmental and operational demands. In recent years, fiber-optic sensors (FOSs) have attracted significant attention for SHM applications due to their immunity to electromagnetic interference, durability in harsh environments, multiplexing capability, and suitability for both localized and fully distributed measurements. In parallel, advances in machine learning (ML) have enabled new approaches for extracting actionable insights from large, high-dimensional sensing datasets. This paper presents a systematic review of FOS-based SHM systems integrated with ML across civil, transportation, energy, marine, and aerospace infrastructures. Following PRISMA 2020 guidelines, peer-reviewed studies were identified and synthesized to examine sensing principles, deployment configurations, data characteristics, and learning-based analytical strategies. Fiber optic technologies are categorized into point-based, quasi-distributed, and fully distributed systems, and their capabilities for capturing strain, temperature, and spatiotemporal structural responses are critically evaluated. ML approaches are examined from a task-oriented perspective, including damage detection, localization, severity assessment, environmental compensation, and prognosis, with emphasis on the alignment between sensing configurations and appropriate learning paradigms. Key challenges remain, particularly regarding large data volumes, environmental variability, limited labeled damage datasets, model generalization, and system-level integration. Emerging directions such as physics-informed and hybrid learning, transfer learning, uncertainty-aware modeling, and integration with digital twins are discussed as pathways toward more robust and scalable SHM systems. By jointly addressing sensing physics and data-driven intelligence, this review provides a structured reference and practical roadmap for advancing intelligent FOS-based SHM in next-generation infrastructure. Full article

With the advancement of digital hydropower stations, the requirements of real-time, high-precision industrial soft measurement of key power equipment operating status are attracting more and more attention. However, it is difficult to transfer energy to the monitoring sensor in strong electromagnetic environments. In this paper, a high-efficiency, high-power-density magnetic field energy harvester is proposed for monitoring sensors in hydropower stations, which captures the energy from the magnetic flux leakage of a hydroelectric generating set. Efficient magnetic energy capture is achieved by modeling material properties and optimizing the receiver’s magnetic core parameters via a Genetic Algorithm. The theoretical analysis of charging characteristics is given, and a Maximum Power Point Tracking (MPPT) control circuit is proposed, realizing high-efficiency energy conversion. Finally, an experimental planet is built. Under 70–130 Gs power-frequency magnetic fields, the system delivers 2.8–5.1 V open-circuit voltage, 66 mW maximum load power, and 6.5 mW/cm³ power density. Full article