Search Results (2,987)

This paper presents the conception, design and real miniature instrument implementation of a dual-purpose sensor for small satellites that can act as a star tracker and space debris detector. In the previous research work, the authors conceived, designed and implemented a breadboard consisting of a computer laptop, a camera interface and camera controller, an image sensor, an optics system, a temperature sensor and a temperature controller. It showed that the instrument was feasible. In this paper, a new real star tracker miniature instrument is designed, physically realized and tested. The implementation follows a New Space approach; it is made with Commercial Off-the-Shelf (COTS) components with space heritage. The instrument’s development, implementation and testing are presented. Full article

Inertial confinement fusion (ICF) stands as one of the approaches to achieve controlled thermonuclear fusion, capable of supplying humans with abundant, economical, and safe energy. In this study, the high-order hybrid compact–WENO scheme is employed to simulate Rayleigh–Taylor instability (RTI) phenomena, one of the challenges hindering the realization of ICF, and to investigate the interaction of RTI phenomena in a multi-layer fluid system. To ensure a more reasonable comparison, the corresponding initial and boundary conditions for three-layer and four-layer fluids are derived based on the same Atwood number. Numerical results show that with the development of RTI phenomena, the interaction between interfaces can be gradually observed. The number of fluid layers exhibits an inhibitory effect on the development of RTI phenomena. When a pair of spike and bubble at two adjacent interfaces reach the same height, the evolution of the spike–bubble gap changes significantly. Full article

In recent years, the traditional orchard sprayer has had problems, such as waste of liquid agrochemicals, low target coverage, high manual dependence, and environmental pollution. In this study, an automatic swing-arm sprayer for orchards was developed based on the standardized pear orchard in Pinggu, Beijing. Firstly, the structural principles of a crawler-type traveling system and swing-arm sprayer were simulated using finite element software design. The combination of a diffuse reflection photoelectric sensor and Arduino single-chip microcomputer was used to realize real-time detection and dynamic spray control in the pear canopy, and the sensor delay compensation algorithm was used to optimize target recognition accuracy and improve the utilization rate of liquid agrochemicals. Through the integration of innovative structural design and intelligent control technology, a vertical droplet distribution test was carried out, and the optimal working distance of the spray was determined to be 1 m; the nozzle angle for the upper layer was 45°, that for the lower layer was 15°, and the optimal speed of the swing-arm motor was 75 r/min. Finally, a particle size test and field test of the orchard sprayer were completed, and it was concluded that the swing-arm mode increased the pear tree canopy droplet coverage by 74%, the overall droplet density by 21.4%, and the deposition amount by 23% compared with the non-swing-arm mode, which verified the practicability and reliability of the swing-arm spray and achieved the goal of on-demand pesticide application in pear orchards. Full article

This paper presents the results of the mathematical modeling and experimental studies of charging a traction lithium-ion battery of a passenger electric car using an integrated charger based on a traction voltage inverter. An original three-stage charging algorithm (3PT/PN) has been developed and implemented, which provides a sequential decrease in the charging current when the specified voltage and temperature levels of the battery module are reached. As part of this study, a comprehensive mathematical model has been created that takes into account the features of the power circuit, control algorithms, thermal effects and characteristics of the storage battery. The model has been successfully verified based on the experimental data obtained when charging the battery module in real conditions. The maximum error of voltage modeling has been 0.71%; that of current has not exceeded 1%. The experiments show the achievement of a realized capacity of 8.9 Ah and an integral efficiency of 85.5%, while the temperature regime remains within safe limits. The proposed approach provides a high charge rate, stability of the thermal state of the battery and a long service life. The results can be used to optimize the charging infrastructure of electric vehicles and to develop intelligent battery module management systems. Full article

To promote the automation and intelligence of rail freight, the accurate identification and localization of bulk cargo unloading hoppers have become a key technical challenge. Under the technological wave driven by the deep integration of Industry 4.0 and artificial intelligence, the bulk cargo unloading process is undergoing a significant transformation from manual operation to intelligent control. In response to this demand, this paper proposes a vision-based 3D localization system for unloading hoppers, which adopts a single visual sensor architecture and integrates three core modules: object detection, corner extraction, and 3D localization. Firstly, a lightweight hybrid attention mechanism is incorporated into the YOLOv5 network to enable edge deployment and enhance the detection accuracy of unloading hoppers in complex industrial scenarios. Secondly, an image processing approach combining depth consistency constraint (DCC) and geometric structure constraints is designed to achieve sub-pixel level extraction of key corner points. Finally, a real-time 3D localization method is realized by integrating corner-based initialization with an RGB-D SLAM tracking mechanism. Experimental results demonstrate that the proposed system achieves an average localization accuracy of 97.07% under challenging working conditions. This system effectively meets the comprehensive requirements of automation, intelligence, and high precision in railway bulk cargo unloading processes, and exhibits strong engineering practicality and application potential. Full article

Autonomous Parking Systems (APSs) are rapidly evolving, promising enhanced convenience, safety, and efficiency. This review critically examines the current strategies in perception, path planning, and vehicle control, alongside system-level aspects like integration, validation, and security. While significant progress has been made, particularly with the advent of deep learning and sophisticated sensor fusion, formidable challenges persist. This paper delves into the inherent trade-offs, such as balancing computational cost with real-time performance demands; unresolved foundational issues, including the verification of non-deterministic AI components; and the profound difficulty of ensuring robust real-world deployment across diverse and unpredictable conditions, ranging from cluttered urban canyons to poorly lit, ambiguously marked parking structures. We also explore the limitations of current technologies, the complexities of safety assurance in dynamic environments, the pervasive impact of cost considerations on system capabilities, and the critical, often underestimated, need for genuine user trust. Future research must address not only these technological gaps with innovative solutions but also the intricate socio-technical dimensions to realize the full potential of APS. Full article

In the operation of a power distribution system, miniature circuit breakers (MCBs) are subjected to the synergistic effect of electrical and mechanical stresses in service, and their operational performance is progressively degraded, which is prone to bring significant losses to the users after failures occur. In order to accurately predict the remaining electrical life of MCBs in service, MCB mechanical characterization and dynamic simulation are carried out, and the initial closing angle of MCBs is selected as the degradation characteristic quantity, so as to deeply analyze the evolutionary characteristics of the initial closing angle in the degradation of MCBs and to construct the electrical degradation model of the one-dimensional linear Wiener process in the present study. With the help of the Monte Carlo method, we carry out the electric life simulation analysis to investigate the intrinsic correlation between the degradation of electric performance and the initial closing angle, and we implement the electric life experiment under the 63 A working condition to analyze the dynamic change in the stiffening angle of the test samples. The parameters of the electrical performance degradation model are identified through the synergistic driving of the electrical life simulation data and the experimental data, the remaining electrical life prediction is realized based on the degradation data of the same batch of products, and the maximum prediction error of the proposed method is controlled within 15%. Full article

Intelligent mining technology, as the core driving force for the digital transformation of the mining industry, integrates cyber-physical systems, artificial intelligence, and industrial internet technologies to establish a “cloud–edge–end” collaborative system. In this paper, the development trajectory of intelligent mining technology has been systematically reviewed, which has gone through four stages: stand-alone automation, integrated automation and informatization, digital and intelligent initial, and comprehensive intelligence. And the current development status of “cloud–edge–end” technologies has been reviewed: (i) The end layer achieves environmental state monitoring and precise control through a multi-source sensing network and intelligent equipment. (ii) The edge layer leverages 5G and edge computing to accomplish real-time data processing, 3D dynamic modeling, and safety early warning. (iii) The cloud layer realizes digital planning and intelligent decision-making, based on the industrial Internet platform. The three-layer collaboration forms a “perception–analysis–decision–execution” closed loop. Currently, there are still many challenges in the development of the technology, including the lack of a standardization system, the bottleneck of multi-source heterogeneous data fusion, the lack of a cross-process coordination of the equipment, and the shortage of interdisciplinary talents. Accordingly, this paper focuses on future development trends from four aspects, providing systematic solutions for a safe, efficient, and sustainable mining operation. Technological evolution will accelerate the formation of an intelligent ecosystem characterized by “standard-driven, data-empowered, equipment-autonomous, and human–machine collaboration”. Full article

This paper addresses the issue of practical fixed-time tracking control for a class of strict-feedback nonlinear systems subject to external disturbances, while ensuring flexible prescribed performance. First, a fixed-time disturbance observer is designed to estimate the unknown external disturbances. The primary advantage of the proposed fixed-time disturbance observer lies in its capability to estimate both the disturbance itself and its higher-order derivatives in fixed time. In addition, various prescribed performance behaviors can be realized via a set of function transformations, merely by modifying certain critical parameters, without the need to redesign the controller. It is shown that, under the proposed control strategy, the system output can track the reference signal in fixed time, and the tracking error always remains within the prescribed performance boundaries. Finally, the simulation results are provided to demonstrate the feasibility and effectiveness of the proposed control scheme. Full article

Optical systems with wide field-of-view (FOV) imaging capabilities are crucial for applications ranging from biomedical diagnostics to remote sensing, yet conventional wide-angle optics face integration challenges in compact platforms. Here, we present the design and experimental demonstration of a single-layer silicon carbide (SiC) metalens achieving a 90° total FOV, whose planar structure and small footprint address the challenges. This design is driven by a gradient-based numerical optimization strategy, Gradient-Optimized Phase Profile Shaping (GOPP), which optimizes the phase profile to accommodate the angle-dependent requirements. Combined with a front aperture, the GOPP-generated phase profile enables off-axis aberration control within a planar structure. Operating at 803 nm with a focal length of 1 mm (NA = 0.25), the fabricated metalens demonstrated focusing capabilities across the wide FOV, enabling effective wide-angle imaging. This work demonstrates the feasibility of using numerical optimization to realize single-layer metalens with challenging wide FOV capabilities, offering a promising route towards highly compact imagers for applications such as endoscopy and dermoscopy. Full article

To deal with the interphase circulating-current problem of modular multilevel converters (MMCs) in multiphase wind power systems, a cooperative circulating-current suppression strategy based on a second-order generalized integrator (SOGI) and passivity-based control–integral sliding mode control (PBC-ISMC) is proposed in this paper. Firstly, a multiphase permanent magnet direct-drive wind power system topology without a step-up transformer is established. On this basis, SOGI is utilized to construct a circulating current extractor, which is utilized to accurately extract the double-frequency component in the circulating current, and, at the same time, effectively filter out the DC components and high-frequency noise. Secondly, passivity-based control (PBC), with its fast energy dissipation, and integral sliding mode control (ISMC), with its strong robustness, are combined to construct the PBC-ISMC circulating-current suppressor, which realizes the nonlinear decoupling and dynamic immunity of the circulating-current model. Finally, simulation results demonstrate that the proposed strategy significantly reduces the harmonic content of the circulating current, optimizes both the bridge-arm current and output current, and achieves superior suppression performance and dynamic response compared to traditional methods, thereby effectively enhancing system power quality and operational reliability. Full article

Traditional industrial robot programming methods often pose high usage thresholds due to their inherent complexity and lack of standardization. Manufacturers typically employ proprietary programming languages or user interfaces, resulting in steep learning curves and limited interoperability. Moreover, conventional systems generally lack capabilities for remote control and real-time status monitoring. In this study, a novel approach is proposed by integrating digital twin technology with traditional robot control methodologies to establish a virtual–real mapping architecture. A high-precision and efficient digital twin-based control platform for industrial robots is developed using the Unity3D (2022.3.53f1c1) engine, offering enhanced visualization, interaction, and system adaptability. The high-precision twin environment is constructed from the three dimensions of the physical layer, digital layer, and information fusion layer. The system adopts the socket communication mechanism based on TCP/IP protocol to realize the real-time acquisition of robot state information and the synchronous issuance of control commands, and constructs the virtual–real bidirectional mapping mechanism. The Unity3D platform is integrated to develop a visual human–computer interaction interface, and the user-oriented graphical interface and modular command system effectively reduce the threshold of robot use. A spatially curved part welding experiment is carried out to verify the adaptability and control accuracy of the system in complex trajectory tracking and flexible welding tasks, and the experimental results show that the system has high accuracy as well as good interactivity and stability. Full article

The Controller Area Network (CAN) protocol is one of the important communication standards in autonomous vehicles, enabling real-time information sharing across in-vehicle (IV) components to realize smooth coordination and dependability in vital activities. Without encryption and authentication, CAN reveals several vulnerabilities related to message attacks within the IV Network (IVN). Traditional centralized Intrusion Detection Systems (IDS) where all the historical data is grouped on one node result in privacy risks and scalability issues, making them unsuitable for real-time intrusion detection. To address these challenges, we propose a Deep Federated Learning (FL) architecture for intrusion detection in IVN. We propose a Bidirectional Long Short Term Memory (BiLSTM) architecture to capture temporal dependencies in the CAN bus and ensure enhanced feature extraction and multi-class classification. By evaluating our framework on three real-world datasets, we show how our proposal outperforms a baseline LSTM model from the state of the art. Full article

Laser propulsion is a new conceptual technology that drives spacecraft and possesses advantages such as high specific impulse, large payload ratio, and low launch cost. It has potential applications in diverse areas, such as space debris mitigation and removal, microsatellite attitude control, and orbital maneuvering. Liquid pulse laser propulsion has notable advantages among the various laser propulsion systems. We review the concept and the theory of liquid laser propulsion. Then, we categorize the current state of research based on three types of propellants—non-energetic liquids, energetic liquids, and liquid metals—and provide an analysis of the propulsion characteristics arising from the laser ablation of liquids such as water, glycidyl azide polymer (GAP), hydroxylammonium nitrate (HAN), and ammonium dinitramide (ADN). We also discuss future research directions and challenges of pulsed liquid laser propulsion. Although experiments have yielded encouraging outcomes due to the distinctive properties of liquid propellants, continued investigation is essential to ensure that this technology performs reliably in actual aerospace applications. Consistent results under both spatial and ground conditions remain a key research content for fully realizing its potential. Full article

The dual-active-bridge (DAB) converter has emerged as a promising topology for renewable energy applications and microgrid systems due to its high power density and bidirectional energy-transfer capability. Enhancing the overall efficiency and reliability of DAB converters requires the simultaneous realization of zero-voltage switching (ZVS) across all switches and the minimization of current stress over wide load and voltage ranges—two objectives that are often in conflict. Conventional modulation strategies with limited degrees of freedom fail to meet these dual goals effectively. To address this challenge, this paper introduces an enhanced integrated optimization strategy based on triple phase shift (EIOS-TPS). This approach formulates the power transmission requirement as an equality constraint and incorporates ZVS and mode boundary conditions as inequalities, resulting in a comprehensive optimization framework. Optimal phase-shift parameters are obtained using the Karush–Kuhn–Tucker (KKT) conditions. To mitigate zero-current switching (ZCS) under a light load and achieve full-range ZVS with reduced current stress, a modulation factor λ is introduced, enabling a globally optimized control trajectory. An experimental 1176 W prototype is developed to validate the proposed method, which achieves full-range ZVS while maintaining low current stress. In the low-power region, it improves efficiency by up to 2.2% in buck mode and 2.0% in boost mode compared with traditional control strategies, reaching a peak efficiency of 96.5%. Full article