Search Results (634)

Monitoring spindle bearing load is essential for ensuring machining accuracy, reliability, and predictive maintenance in machine tools. This paper presents an approach that combines drive-based cutting force estimation with a finite element method (FEM) spindle model. The drive-based method reconstructs process forces from the motor torque signal of the feed axes by modeling and compensating motion-related torque components, including static friction, acceleration, gravitation, standstill, and periodic disturbances. The inverse mechanical and control transfer behavior is also considered. Input signals include the actual motor torque, axis position, and position setpoint, recorded by the control system’s internal measurement function at the interpolator clock rate. Cutting forces are then calculated in MATLAB/Simulink and used as inputs for the FEM spindle model. Rolling elements are replaced by bushing joints with stiffness derived from datasheets and adjusted through experiments. Force estimation was validated on a DMC 850 V machining center using a standardized test workpiece, with results compared against a dynamometer. The spindle model was validated separately on a MCV 754 Quick machine under static loading. The combined approach produced consistent results and identified the front bearing as the most critically loaded. The method enables practical spindle bearing load estimation without external sensors, lowering system complexity and cost. Full article

We propose and demonstrate a novel motion blur-free hybrid image sensing technique. Unlike the previous hybrid image sensors, we developed a homogeneous hybrid image sensing technique including 60 fps CMOS Image Sensor (CIS) and 1440 fps pseudo Dynamic Vision Sensor (DVS) image frames without any performance degradation caused by static bad pixels. To achieve the fast readout, we implemented two one-side ADCs on two photodiodes (PDs) and the pixel output settling time can be reduced significantly by using the column switch control. The high-speed pseudo DVS frame can be obtained by differentiating fast-readout CIS frames, by which, in turn, the world’s smallest pseudo DVS pixel (1.8 μm) can be achieved. In addition, we confirmed that CIS (50 Mp resolution) and DVS (0.78 Mp resolution) data obtained from the hybrid image sensor can be transmitted over the MIPI (4.5 Gb/s four-lane D-PHY) interface without signal loss. The results showed that the motion blur of a 60 fps CIS frame image can be compensated dramatically by using the proposed pseudo DVS frames together with a deblur algorithm. Finally, using the event simulation, we verified that a 1440 fps pseudo DVS frame can compensate the motion blur of the CIS image captured in the situation of jogging at a 3 m distance. Full article

The contact fatigue performance of carburized gear steels is critical for transmission durability, yet the mechanisms linking alloy-specific microstructure to failure modes remain complex. This study systematically compares the contact fatigue behaviors of 20MnCr5 and 20CrMoH gears using step-loading tests and multi-scale characterization. The results demonstrate a significantly higher contact fatigue limit for 20MnCr5 of 1709 ± 12 MPa compared to 1652 ± 40 MPa for 20CrMoH, despite the latter exhibiting higher initial surface hardness. This hardness–toughness paradox is mechanistically elucidated by the distinct roles of alloying elements: while Molybdenum in 20CrMoH refines the grain size for high static strength, it limits retained austenite stability, resulting in a brittle hard-shell and soft-core structure prone to interface decohesion at martensite lath boundaries. Conversely, Manganese in 20MnCr5 promotes a gentler hardness gradient via favorable diffusion kinetics and stabilizes abundant film-like retained austenite. This microstructure activates a Stress Compensation Mechanism, where strain-induced martensitic transformation generates compressive volume expansion to counteract cyclic stress relaxation. Consequently, 20MnCr5 exhibits mild plastic micropitting driven by transformation toughening, whereas 20CrMoH undergoes severe brittle spalling driven by the Eggshell Effect. These findings confirm that balancing matrix toughness with hardness is more critical than maximizing surface hardness alone for contact fatigue resistance. Full article

To address the challenges of low automatic leveling efficiency and insufficient control precision for small tracked operation chassis navigating uneven terrain in hilly and mountainous areas, this study proposes a leveling control system that integrates a dual-layer threshold strategy with a BP neural network algorithm. The system is developed based on a four-point lifting leveling mechanism. Building upon this foundation, the conventional single-threshold angle error compensation control strategy was optimized to meet the specific leveling demands of chassis operating in such complex environments. A co-simulation platform was established using Matlab/Simulink-AMEsim for subsequent simulation and comparative analysis. Simulation results demonstrate that the proposed method achieves a 15.6% improvement in leveling response speed and a 21.3% enhancement in leveling accuracy compared to the classical single-threshold PID control algorithm. Static test results reveal a smooth leveling process devoid of significant overshoot or hysteresis, with the leveling error consistently maintained within 0.5°. Field tests further indicate that at a travel speed of 3 km/h under a 50 kg load, the platform stabilization time is reduced by an average of 1.3 s, while the leveling angle error remains within 0.5°. The proposed system not only improves leveling response speed and precision but also effectively enhances the overall leveling efficiency of the tracked chassis system. Full article

To meet the growing demand for quantitative remote sensing applications in GIIRS radiometric calibration, this paper proposes a temperature field-driven adaptive scan mirror thermal radiation interference correction method. Based on the on-orbit deep space observation data from the Fengyun-4B satellite, this paper systematically analyzes the thermal radiation interference characteristics caused by scan mirror deflection and constructs the first scan mirror thermal radiation response model suitable for GIIRS. On the basis of this model, this paper further introduces the dynamic variation characteristics of the internal thermal environment of the instrument, enabling adaptive response and compensation for radiation disturbances. This method overcomes the limitations of relying on static calibration parameters and improves the generality and robustness of the model. Independent validation results show that this method effectively suppresses the interference of scan mirror deflection on instrument background radiation and enhances the consistency of the deep space and blackbody spectral diurnal variation time series. After correction, the average system bias of the interference-sensitive channel decreased by 94%, and the standard deviation of radiance bias from 2.5 mW/m²·sr·cm⁻¹ to below 0.5 mW/m²·sr·cm⁻¹. In the O-B test, the maximum improvement in relative standard deviation reached 0.15 K. Full article

Current upper-limb rehabilitation robots primarily focus on training tasks involving free movements or static interactions with rigid objects. These paradigms lack simulation of complex object manipulation tasks encountered in daily life, thereby limiting the training of patients’ high-level sensorimotor integration capabilities. To address this gap, this study proposes an innovative robotic rehabilitation training system designed for functional occupational therapy. Specifically, the task of transporting a water cup was abstracted into a cup–ball system integrated with a robotic arm. The ball was modeled as a point mass, and kinematic and dynamic analyses of the system were conducted. A visual tracking method was employed to monitor the ball’s motion and calculate its slosh angle. Owing to the impaired fine motor control in stroke patients, a sloshing suppression control strategy integrating exponential filtering, feedforward force compensation, and impedance control was proposed to prevent the ball from spilling. Experiments validated the effectiveness of the proposed method. The results indicated that with full compensation, the oscillation rate of the ball was significantly reduced, and the smoothness of the hand force was markedly improved. This study presents an effective method for addressing dynamic uncertainty in rehabilitation robot training, thus significantly improving the functional relevance of the training. Full article

This paper proposes a coordinated hybrid VAR compensation strategy that leverages the dynamic support capabilities of a grid-forming (GFM) battery energy storage system (BESS) and solar photovoltaic (PV) plant to enhance the stability of inverter-dominated power systems. The hybrid compensator integrates a VSC-based static synchronous compensator (STATCOM) with a thyristor-switched capacitor (TSC), combining the fast dynamic response of the STATCOM with the high reactive power capacity of the TSC. A coordinated control framework is developed to enable seamless interaction between the hybrid VAR compensator and the GFM-controlled PV and BESS units, ensuring improved voltage regulation and transient stability under varying operating conditions. The PV plant operates at maximum power Point while maintaining its grid-forming capability, thereby maximizing renewable energy utilization while contributing to frequency and voltage support. The effectiveness of the proposed strategy is validated through FPGA-based real-time simulations under scenarios including large load variations, solar irradiance fluctuations, and grid disturbances. Results show that the coordinated operation enhances voltage stability, strengthens reactive power support, mitigates low-frequency oscillations, and significantly improves the dynamic performance of low-inertia, inverter-dominated grids. Full article

In harsh marine environments, during the operation of the Ship–Cable–Body coupled system, the towed cable may become slack or taut, and tension oscillations may occur, leading to cable breakage or launch and recovery system (LARS) damage, underscoring the need for effective compensation control. Traditional offline and static simulation methods fail to capture the system’s dynamics, leading to inaccurate validation of control strategies. To address this, we propose a real-time dynamic modeling framework using the OrcFxAPI, enabling millisecond-level bidirectional interaction between the towed body’s motion and LARS commands. By integrating a Python 3.10-based PID controller with OrcFxAPI, the framework achieves real-time active heave compensation (AHC) in deep-sea towing, dynamically adjusting cable length and payout speed based on feedback to suppress vibrations. Unlike prior studies focused on launch and recovery, this work systematically evaluates AHC performance during typical operations (hovering, linear and turning motion), and compares system responses with and without compensation. Results show the AHC framework significantly improves towed body stability, reduces tension fluctuations, and keeps tension within safe working limits (SWLs), while identifying critical cable payout speed thresholds for practical operation. The approach validates the use of OrcFxAPI for high-fidelity real-time coupling analysis and provides a reliable tool for optimizing control and design of deep-sea towing systems. Full article

Voltage instability and power quality degradation represent critical barriers to the reliable operation of modern wind farm-based microgrids. As the share of distributed wind generation continues to grow, fluctuating wind speeds and variable reactive power demands increasingly challenge grid stability. This study proposes an adaptive decentralized framework integrating a Dynamic Distribution Static Compensator (DSTATCOM) with an Artificial Neuro-Fuzzy Inference System (ANFIS)-based control strategy to enhance dynamic voltage and frequency stability in wind farm microgrids. Unlike conventional centralized STATCOM configurations, the proposed system employs parallel wind turbine modules that can be selectively switched based on voltage feedback to maintain optimal grid conditions. Each turbine is connected to a capacitive circuit for real-time voltage monitoring, while the ANFIS controller adaptively adjusts compensation signals to ensure minimal voltage deviation and reduced harmonic distortion. The framework was modeled and validated in the MATLAB/Simulink R2023a environment using the Simscape Power Systems toolbox. Simulation results demonstrated superior transient response, voltage recovery, and power factor correction compared with traditional PI and fuzzy-based controllers, achieving a total harmonic distortion below 2.5% and settling times under 0.5 s. The findings confirm that the proposed decentralized DSTATCOM–ANFIS approach provides an effective, scalable, and cost-efficient solution for maintaining dynamic stability and high power quality in wind farm based microgrids. Full article

Integration of renewable energy sources into existing residential and communal district heating systems requires technical adjustments and corrections. Measures aimed at reducing heat consumption at the points of delivery have a similar impact. This study aims, through simplified partial models (in heating mode), to present the relationships between these modifications and their potential effects on operational problems and deficiencies. The main parameters assessed in the design and correction of systems are temperature differentials, derived flow rates, pumping work, and control methods. Within the chain of heat source–primary distribution–secondary distribution–consumers, the analysis focuses on secondary circuits with consumers. A simplified multi-building network model was used to compare static and dynamic control strategies under temperature regimes of 70/50 °C, 60/40 °C, and 40/30 °C. The results show that dynamic control based on variable-frequency pumps, weather-compensated supply regulation, and optimized temperature differences between supply and return lines (ΔT) reduces pumping energy by 30–40% and increases heat delivery efficiency by up to 10%. A significant reduction in CO₂ emissions is also observed due to decreased pumping work, reduced heat losses in the distribution network, and the integration of renewable energy sources. The savings depend on the type and extent of RES utilization. The implementation of dynamic control in these systems significantly improves exergy efficiency, operational stability, and the potential for low-temperature operation, thus providing a practical framework for the modernization of district heating networks. Full article

The planning of unbalanced three-phase distribution networks increasingly requires the coordinated integration of distributed energy resources, such as photovoltaic (PV) generators and static compensators (D-STATCOMs), to enhance system performance and reduce costs. This planning task is inherently challenging, as it leads to a mixed-integer nonlinear optimization problem driven by nonconvex voltage–current–power relationships, phase unbalances, and the temporal variability of demand and solar irradiance. This work proposes an exact Mixed-Integer Nonlinear Programming (MINLP) framework for the joint siting and sizing of PV units and D-STATCOM devices, with an objective function based on the minimization of the equivalent annual cost of energy purchases and investments. The methodology is applied to 25- and 37-bus unbalanced test systems and benchmarked against four state-of-the-art metaheuristic algorithms. The results show that the exact MINLP consistently attains the global optimum, yielding reductions in equivalent annual cost of USD 392,855 (14.36%) and USD 436,361 (14.90%) for the respective test systems, whereas the metaheuristics provide near-optimal but slightly dispersed solutions. These findings highlight the potential of exact optimization as a robust and economically sound tool for long-term distribution network planning, combining technical reliability with guaranteed global optimality. Full article

Composite materials have been extensively used across numerous industries due to their exceptional specific strength and corrosive resistance. However, ensuring their mechanical performance and structural integrity remains a critical challenge. This study provides an in-depth investigation into the damage mechanisms occurring in composite rebars manufactured via a modified pultrusion process, with a special emphasis on carbon, glass, and hybrid continuous fiber-reinforced polymers with epoxy resin matrix subjected to static tensile loading. To reveal the damage development, the acoustic emission (AE) technique was employed. Given the inherent complexity of composite microstructures, multiple failure modes can occur simultaneously, often masked by background noise and attenuation effects. Therefore, the core objective of this research is to evaluate and quantify the influence of acoustic attenuation on damage assessment in composite materials. This study introduces an optimization approach to minimize discrepancies between signals captured by different sensors, thereby enhancing the reliability of AE data interpretation. Results reveal that attenuation is strongly dependent on signal travel distance, frequency spectrum, and sensor type. Importantly, a data correction methodology is proposed to mitigate these effects, improving the accuracy of damage detection. Among the analyzed AE parameters, the initial frequency emerged as the most reliable feature for identifying the origin of acoustic events within hybrid composite structures. This finding represents a significant step toward more precise, attenuation-compensated acoustic emission monitoring, offering improved insight into failure mechanisms and contributing to the development of smarter diagnostic tools for composite materials. Full article

The goal of the study is to inquire into how longer tenure on the board may undermine directors’ independence and distort the efficiency of executive compensation mechanisms. Our empirical findings based on an international panel database and static panel regression modeling demonstrate that director tenure is positively associated with executive compensation with the effect being amplified by the degree of managerial capture of the board. Longer director tenure is also shown to reduce the sensitivity of executive compensation to negative earnings surprises while simultaneously contributing to the lower overall probability of management departures even in the event of a negative earnings surprise. Board independence is evidenced to play no significant role in intermediating the studied relationships. Overall, while postulating the existence of an independence–tenure tradeoff, the paper posits a need for revision of the currently applicable formal criteria of board independence in order for them to accommodate the possible impact of director tenure on the quality of corporate oversight. The present study extends upon the existing literature by expanding the geographical scale of the sample and focusing on indirect symptoms of reduced supervisory effectiveness of the boards. Full article

Pedestrian trajectory prediction from a vehicle-mounted perspective is essential for autonomous driving in complex urban environments yet remains challenging due to ego-motion jitter, frequent occlusions, and scene variability. Existing approaches, largely developed for static surveillance views, struggle to cope with continuously shifting viewpoints. To address these issues, we propose V-PTP-IC, an end-to-end framework that stabilizes motion, models inter-agent interactions, and fuses multi-modal cues for trajectory prediction. The system integrates Simple Online and Realtime Tracking (SORT)-based tracklet augmentation, Scale-Invariant Feature Transform (SIFT)-assisted ego-motion compensation, graph-based interaction reasoning, and multi-head attention fusion, followed by Long Short-Term Memory (LSTM) decoding. Experiments on the JAAD and PIE datasets demonstrate that V-PTP-IC substantially outperforms existing baselines, reducing ADE by 27.23% and 25.73% and FDE by 33.88% and 32.85%, respectively. This advances dynamic scene understanding for safer autonomous systems. Full article

Power quality is a continuous concern in industry, especially in steel mills operating with nonlinear, fluctuating, and unbalanced loads. This paper investigates the influence of a Static Var Compensator (SVC) on power quality parameters in a hot metallurgical rolling mill. The study includes experimental measurements performed under real operating conditions, both with and without reactive power compensation. The measurements included voltage and current waveforms, active and reactive power, total harmonic distortion (THD), and the power factor, recorded both with and without a Static Var Compensator (SVC) in operation. The results show that in the presence of an SVC, voltage stability was improved and reactive power flow was reduced, although the current harmonic distortion remained above the recommended limits (ATHD > 40%). Despite these limitations, the voltage THD (VTHD) remained within acceptable ranges, as the upstream network maintained voltage levels despite the harmonic injection. The results obtained emphasize the effectiveness of SVCs in reducing reactive power while highlighting the need for complementary strategies to mitigate harmonics due to the presence of converters. These conclusions are particularly relevant for industrial installations that want to improve power quality and energy efficiency through specific compensation technologies. Full article