Search Results (506)

The high incidence of melanoma leading to a poor prognosis rate endorses the development of alternative and innovative approaches in the treatment of melanoma. Therefore, the present study aims to develop and characterize, in terms of physicochemical features and biological impact, an aqueous suspension of magnetite (Fe₃O₄) coated with β-cyclodextrin (Fe₃O₄@β-CD) as a potential innovative alternative nanosystem for melanoma therapy. The nanosystem exhibited physicochemical characteristics suitable for biological applications, revealing a successful complexation of Fe₃O₄ NPs with β-CD and an average size of 18.1 ± 2.1 nm. In addition, the in vitro evaluations revealed that the newly developed nanosystem presented high biocompatibility on a human keratinocyte (HaCaT) monolayer and selective antiproliferative activity on amelanotic human melanoma (A375) cells, inducing early apoptosis features when concentrations of 10, 15, and 20 μg/mL were employed for 48 h and 72 h. Collectively, the Fe₃O₄@β-CD nanosystem reveals promising features for an adjuvant approach in melanoma treatment, mainly due to its β-cyclodextrin coating, thus endorsing a potential co-loading of therapeutic drugs. Furthermore, the intrinsic magnetic core of Fe₃O₄ NPs supports the magnetically based cancer treatment strategies. Full article

Over the past decade, the number and diversity of identified protein post-translational modifications (PTMs) have grown significantly. However, most PTMs occur at relatively low abundance, making selective enrichment of modified peptides essential. To address this, we developed a thermodynamic model describing the free beads enrichment in suspension enrichment process and derived a theoretical relationship between material dosage and analyte recovery. The model predicts a non-linear trend, with enrichment efficiency increasing up to an optimal dosage and declining thereafter—a pattern confirmed by experimental data. We validated the model using centrifugation-based enrichment for glycosylated peptides and magnetic-based enrichment for phosphorylated peptides. In both cases, the results aligned with theoretical predictions. Additionally, the optimal dosage varied among peptides with the same modification type, highlighting the importance of tailoring enrichment strategies. This study provides a solid theoretical and experimental basis for optimizing PTMs enrichment and advancing more sensitive, accurate, and efficient mass spectrometry-based proteomic workflows. Full article

Bearingless interior permanent magnet synchronous motors (BIPMSMs) have received considerable attention in recent research due to their advantages of high speed, high power density, and absence of mechanical wear. In order to improve the torque and suspension performance of the BIPMSM, an optimization design method of BIPMSM is proposed in this paper based on sensitivity analysis, response surface fitting, and the multi-objective whale optimization algorithm (MOWOA). Firstly, the structure and operation principle of the BIPMSM are introduced. Secondly, significant variables are extracted based on sensitivity analysis. Then, regression equations of the significant variables and optimization objectives are fitted by the response surface method, and global optimization is performed with MOWOA. Finally, the motor performance before and after optimization is compared. The results demonstrate that the proposed multi-objective optimization design scheme can significantly improve the performance of the BIPMSM and effectively shorten the design cycle. Full article

At present, the redundant structures are one of the most effective methods for solving magnetic levitation bearing coil failure. Coil failure causes residual effective magnetic poles to form different support structures and even asymmetrical structures. For the magnetic bearing with redundant structures, how to construct the electromagnetic force (EMF) that occurs under different support structures to achieve support reconstruction is the key to realizing fault tolerance control. To reveal the support reconstruction mechanism of magnetic bearing with a redundant structure, firstly, this paper takes a single-degree-of-freedom magnetic suspension body as an example to conduct a linearization theory analysis of the offset current, clarifying the concept of the current distribution matrix (CDM) and its function; then, the nonlinear EMF mode of magnetic bearing with an eight-pole is constructed, and it is linearized by using the theory of bias current linearization. Furthermore, the conditions of no coils fail, the 8th coil fails, and the 6–8th coils fail are considered, and, with the maximum principle function of EMF, the corresponding current matrices are obtained. Meanwhile, based on the CDM, the corresponding magnetic flux densities were calculated, proving that EMF reconstruction can be achieved under the three support structures. Finally, with the CDM and position control law, a fault-tolerant control system was constructed, and the simulation of the magnetic bearing with a redundant structure was carried out. The simulation results reveal the mechanism of support reconstruction with three aspects of rotor displacement, the value and direction of currents that occur in each coil. The simulation results show that, in the 8-pole magnetic bearing, this study can achieve support reconstruction in the case of faults in up to two coils. Under the three working conditions of wireless no coil failure, the 8th coil fails and the 6–8th coils fail, the current distribution strategy was adjusted through the CDM. The instantaneous displacement disturbance during the support reconstruction process was less than 0.28 μm, and the EMF after reconstruction was basically consistent with the expected value. Full article

With the launch of the Artemis program and the International Lunar Research Station project, the construction of lunar bases has emerged as a global research focus. In situ manufacturing technologies for robust lunar regolith-based building materials are critical to ensuring building safety under the Moon’s extreme environmental conditions. This paper reviews the relevant advancements in two areas: solidification technologies for lunar regolith-based construction materials and simulation techniques of extreme lunar environments. This review reveals that, although significant advancements have been made in solidification technologies, the development of lunar environment simulation technologies, particularly for 1/6 g gravity, has lagged, thereby hindering the assessment of the in situ applicability of these solidification methods. To address these limitations, this paper introduces a newly developed comprehensive lunar extreme environment simulation system based on superconducting magnetic suspension technology and its potential applications in lunar regolith-based construction material solidification. This review highlights the current progress and challenges in solidification techniques for lunar regolith-based building materials, aiming to enhance researchers’ attention to the extreme environmental conditions on the lunar surface. Full article

This study discloses the noncovalent immobilization of a bienzyme cascade composed of glucose oxidase (GOx) and horseradish peroxidase (HRP) onto magnetically responsive polyamide microparticles (PA MPs). Porous PA6, PA4, and PA12 MPs containing iron fillers were synthesized via activated anionic ring-opening polymerization in suspension, alongside neat PA6 MPs used as a reference. Four hybrid catalytic systems (GOx/HRP@PA) were prepared through sequential adsorption of HRP and GOx onto the various PA MP supports. The initial morphologies of the supports and the hybrid biocatalysts were characterized by SEM, followed by evaluation of the catalytic performance using a two-step glucose oxidation cascade process. Among all systems, the GOx/HRP@PA4-Fe complex exhibited the highest activity, being approximately 1.5 times greater than the native enzyme dyad, followed by the PA6-supported system with slightly inferior performance. All systems obeyed Michaelis–Menten kinetics, with the immobilized cascades displaying higher Kₘ and Vₘₐₓ values than the non-immobilized enzyme pair while maintaining comparable catalytic efficiencies, CE (CE = k_cat/Kₘ). Subsequently, the immobilized and native enzyme systems were employed for the polymerization of aniline. According to UV–VIS, complete monomer conversion was achieved within 24 h for selected catalysts, and FTIR analysis confirmed the formation of polyaniline in the emeraldine base form without the use of template molecules. These findings highlight the potential of Fe-containing polyamide microparticles as efficient supports for the sustainable, enzyme-mediated synthesis of intrinsically conductive aromatic polymers. Full article

In response to the challenges associated with weld treatment during the on-site corrosion protection of hydraulic steel gates, this paper proposes a method utilizing a magnetic adsorption climbing robot to perform corrosion protection operations. Firstly, a magnetic adsorption climbing robot with a multi-wheel independent drive configuration is proposed as a mobile platform. The robot body consists of six joint modules, with the two middle joints featuring adjustable suspension. The joints are connected in series via an EtherCAT bus communication system. Secondly, the kinematic model of the climbing robot is analyzed and a PID trajectory tracking control method is designed, based on the kinematic model and trajectory deviation information collected by the vision system. Subsequently, the proposed kinematic model and trajectory tracking control method are validated through Python3 simulation and actual operation tests on a curved trajectory, demonstrating the rationality of the designed PID controller and control parameters. Finally, an intelligent software system for weld defect detection based on computer vision is developed. This system is demonstrated to conduct defect detection on images of the current weld position using a trained model. Full article

The permanent magnet electrodynamic suspension system (PMEDS) has demonstrated significant advantages in high-speed and ultra-high-speed applications due to its simple structure, low cost, and stable levitation force. However, the weak damping characteristic remains a critical issue limiting its practical implementation. This work investigates a passive damping plate utilizing the end field of onboard magnets, focusing on magnet-damping plate optimization and vehicle dynamics. Firstly, the configuration, operation principles, and electromagnetic parameters of the PMEDS vehicle are elucidated. Secondly, the dependences of magnet-conductive plate specifications on the damping force are examined. An optimization index based on the levitation-to-damping force ratio is proposed to enable collaborative optimization of magnet and conductive plate parameters. Finally, the vehicle dynamic model is developed using Simpack software to investigate payload and speed effects on dynamic responses under random track excitation, validating the effectiveness of the proposed passive damping solution. This study provides technical references for the design, engineering applications, and performance evaluation of passive damping schemes in PMEDS vehicles. Full article

This study focuses on a blood pump system equipped with four radial active magnetic bearings (RAMBs). The finite element method (FEM) was employed to optimize the physical parameters of the system. Based on this optimization, two intelligent PID tuning strategies—particle swarm optimization (PSO) and backpropagation (BP) neural networks—were compared. First, a differential control model of a single-degree-of-freedom active magnetic bearing was developed, based on the topology and operating principles of the radial magnetic bearings. Then, magnetic circuit parameters were precisely identified through finite element simulation, enabling accurate optimization of the physical model. To enhance control accuracy, intelligent tuning strategies based on PSO and BP neural networks were applied, effectively addressing the limitations of conventional PID controllers, which often rely on empirical tuning and lack precision. Finally, simulation experiments were conducted to evaluate the optimization performance of PSO and BP neural networks in the magnetic bearing control system. The results demonstrate that the improved PSO algorithm offers significant advantages over both the BP neural network and traditional manual PID tuning. Specifically, it achieved a rise time of 0.0049 s, a settling time of 0.0079 s, and a steady-state error of 0.0013 mm. The improved PSO algorithm ensures system stability while delivering faster dynamic response and superior control accuracy. Full article

The authors have designed a gyro-system for orientation (guidance) and stabilization, with two gimbals and a rotor in magnetic suspension (AMB—Active Magnetic Bearing) usable for self-guided rockets. The gyro-system (DGMSGG—double gimbal magnetic suspension gyro-system for guidance) orients and stabilizes the target coordinator’s axis (CT) and, at the same time, the AMB–rotor’s axis so that they overlap the guidance line (the target line). DGMSGG consists of two decoupled systems: one for canceling the AMB–rotor translations along the precession axes (induced by external disturbing forces), the other for canceling the AMB–rotor rotations relative to the CT-axis (induced by external disturbing moments) and, at the same time, for controlling the gimbals’ rotations, so that the AMB–rotor’s axis overlaps the guidance line. The nonlinear DGMSGG model is decomposed into two sub-models: one for the AMB–rotor’s translation, the other for the AMB–rotor’s and gimbals’ rotation. The second sub-model is described first by nonlinear state equations. This model is reduced to a second order nonlinear matrix—vector form with respect to the output vector. The output vector consists of the rotation angles of the AMB–rotor and the rotation angles of the gimbals. For this purpose, a differential geometry method, based on the use of the output vector’s gradient with respect to the nonlinear state functions, i.e., based on Lie derivatives, is used. This equation highlights the relative degree (equal to 2) with respect to the variables of the output vector and allows for the use of the dynamic inversion method in the design of stabilization and guidance controllers (of P.I.D.- and PD-types), as well as in the design of the related linear state observers. The controller of the subsystem intended for AMB–rotor’s translations control is chosen as P.I.D.-type, which leads to the cancellation of both its translations and its translation speeds. The theoretical results are validated through numerical simulations, using Simulink/Matlab models. Full article

This study addresses the challenge of ride height control in linear motor-based active suspension systems by proposing a control strategy based on linear active disturbance rejection control (LADRC). The effectiveness of the proposed approach is experimentally validated using a high-precision test platform built on the NI cRIO-9014 real-time controller. The platform integrates a permanent magnet synchronous linear motor, a motor driver, acceleration sensors, and a vibration control system to realize closed-loop control of vehicle body height. Experimental results demonstrate that, compared with conventional PID control, LADRC achieves superior performance in height regulation accuracy, dynamic responsiveness, vertical acceleration suppression, and steady-state stability. In step response experiments, LADRC reduces the regulation time by 53.8% (from 1.3 s to 0.6 s) and lowers the steady-state error from 0.502 mm to 0.05 mm. In sinusoidal trajectory tracking tests, the LADRC approach reduces peak and RMS tracking errors by 81.5% and 80.3%, respectively. Moreover, under random road excitation, LADRC effectively attenuates high-frequency body vibrations, with reductions of 29.58% in peak vertical acceleration and 12.23% in RMS acceleration. Full article

This study introduces a flywheel rotor support structure for an active magnetic suspension flywheel energy storage system. In this structure, there is an axial offset between the axial-bearing position and the mass-center of the flywheel rotor, which affects the tilting rotation of the flywheel rotor and which causes the coupling between its tilting rotation and radial motion. Therefore, the influence of the bearing position on the vibration characteristics of the flywheel rotor is explored in this paper. The tilting rotation constraint of the flywheel rotor by axial active magnetic bearing (AAMB) is analyzed, and the radial active magnetic bearing (RAMB) is equivalently treated with dynamic stiffness and dynamic damping. Based on this, a dynamic model of the active magnetic suspension rigid flywheel rotor, considering the position parameter of the axial bearing, is established. To quantify the axial offset between the position of the AAMB and the mass-center of the flywheel rotor, the axial-bearing position offset ratio γ is defined. The variation trend of the vibration characteristics of flywheel rotor with γ is discussed, and its correctness is validated through experiments. It is indicated that, with the increase of γ, the second-order positive precession frequency of the flywheel rotor decreases obviously, and the influence of the gyroscope torque gradually weakens. Meanwhile, its second-order critical speed ω_2c decreases significantly (when γ is 0.5, ω_2c decreases by about 62%); ω_2c corresponds to the inclined mode, revealing that the offset ratio γ has a prominent influence on the critical speed under this mode. In addition, as γ increases, the mass unbalance response amplitude of the flywheel rotor under the speed of ω_2c decreases significantly. The reasonable design of the axial-bearing position parameter can effectively improve the operational stability of the active magnetic suspension flywheel energy storage system. Full article

In power inspection fields, snake-like robots are often used for transmission line inspection tasks, requiring accurate identification of various power fittings. However, traditional visual sensors perform poorly under varying light intensity and complex background conditions. This paper proposes a non-visual perception method for the high-precision classification of different power fittings (e.g., vibration dampers, suspension clamps, and tension clamps) in snake-like robot transmission line inspection for high-voltage lines. This method, unaffected by light intensity changes, uses machine learning to classify the magnetic induction electromotive force signals around the fittings. First, the Dodd–Deeds eddy current model is used to analyse the magnetic field changes around the transmission line fittings and determine the induction coil distribution. Then, the concept of condition number and singular value decomposition (SVD) are introduced to analyse the impact of detection position on classification accuracy, with optimal detection positions found using the particle swarm optimization algorithm. Finally, a BP neural network optimised by a genetic algorithm is used for power fitting identification. Experiments show that this method successfully identifies vibration dampers, tension clamps, suspension clamps, and transmission lines at detection distances of 5 cm, 10 cm, 15 cm, and 20 cm, with accuracies of 99.8%, 97.5%, 95.1%, and 92.5%, respectively. Full article

Magnetic pulse welding (MPW) is a promising solid-state joining process that utilizes electromagnetic forces to create high-speed, impact-like collisions between two metal components. This welding technique is widely known for its ability to join dissimilar metals, including aluminum, steel, and copper, without the need for additional filler materials or fluxes. MPW offers several advantages, such as minimal heat input, no distortion or warping, and excellent joint strength and integrity. The process is highly efficient, with welding times typically ranging from microseconds to milliseconds, making it suitable for high-volume production applications in sectors including automotive, aerospace, electronics, and various other industries where strong and reliable joints are required. It provides a cost-effective solution for joining lightweight materials, reducing weight and improving fuel efficiency in transportation systems. This contribution concerns an application for the automotive sector (body-in-white) and specifically examines the welding of AA6082-T6 aluminum alloy with HC420LA cold-rolled micro-alloyed steel. One of the main aspects for MPW optimization is the determination of the process window that does not depend on the equipment used but rather on the parameters associated with the physical mechanisms of the process. It was demonstrated that process windows based on contact angle versus output voltage diagrams can be of interest for production use for a given component (shock absorbers, suspension struts, chassis components, instrument panel beams, next-generation crash boxes, etc.). The process window based on impact pressures versus impact velocity for different impact angles, in addition to not depending on the equipment, allows highlighting other factors such as the pressure welding threshold for different temperatures in the impact zone, critical transition speeds for straight or wavy interface formation, and the jetting/no jetting effect transition. Experimental results demonstrated that optimal welding conditions are achieved with impact velocities between 900 and 1200 m/s, impact pressures of 3000–4000 MPa, and impact angles ranging from 18–35°. These conditions correspond to optimal technological parameters including gaps of 1.5–2 mm and output voltages between 7.5 and 8.5 kV. Successful welds require mean energy values above 20 kJ and weld specific energy values exceeding 150 kJ/m². The study establishes critical failure thresholds: welds consistently failed when gap distances exceeded 3 mm, output voltage dropped below 5.5 kV, or impact pressures fell below 2000 MPa. To determine these impact parameters, relationships based on Buckingham’s π theorem provide a viable solution closely aligned with experimental reality. Additionally, shear tests were conducted to determine weld cohesion, enabling the integration of mechanical resistance isovalues into the process window. The findings reveal an inverse relationship between impact angle and weld specific energy, with higher impact velocities producing thicker intermetallic compounds (IMCs), emphasizing the need for careful parameter optimization to balance weld strength and IMC formation. Full article

High production costs and extended development timelines pose significant challenges to the manufacturing of bearingless permanent magnet synchronous motors (BPMSMs). Moreover, uncertainties regarding the motor’s ability to generate suspension and torque often persist even after prototyping, primarily due to the limitations of lumped parameter models in capturing the system’s complex dynamics. Since this technology is not yet fully consolidated, there is a clear need for a solution that enables the effective evaluation of BPMSMs prior to physical production. To address this, a reduced-order model (ROM) was developed for BPMSMs with combined windings, capturing the cross-coupling effects associated with rotor eccentricity, magnetic saturation, and topological complexity. The model was constructed using the parametric interpolation method (PIM), enabling efficient and accurate representations of nonlinear electromechanical behavior as ferromagnetic materials and spatial harmonics are addressed through finite element modeling. Additionally, hardware-in-the-loop (HIL) techniques were used for gain tuning, and active disturbance rejection control (ADRC) was applied to enhance performance. This combined approach offers a comprehensive solution for the design and control of BPMSMs. Full article