Search Results (13,453)

A novel hybrid ISSA-GWO (Improved Sparrow Search Algorithm–Grey Wolf Optimizer) is proposed for the path planning of Unmanned Wing-in-Ground-Effect Craft (UWIGC), integrating ground-effect constraints and island-reef environments into a unified optimization framework. Leveraging its exceptional ultra-low-altitude flight capability and high economic efficiency, the UWIGC offers unique advantages in maritime missions such as island patrol and rapid replenishment. However, its path planning faces the dual challenge of precise obstacle avoidance and ultra-low-altitude maintenance, due to the obstacle distribution in island regions and the altitude window constraints inherent to ground-effect flight. To address this, the proposed method integrates the swarm intelligence of the Sparrow Search Algorithm and employs a self-destruction mechanism to escape local optima. Furthermore, it combines the hierarchical guidance of the Grey Wolf Optimizer to enhance convergence accuracy. The algorithm incorporates ground-effect maintenance constraints and an island-reef threat model, and it smooths the final path using cubic B-spline curves. Simulation results demonstrate that the proposed algorithm outperforms the standard Sparrow Search Algorithm, Grey Wolf Optimizer, and Particle Swarm Optimization in terms of convergence speed, optimization accuracy, and obstacle avoidance success rate. It is capable of generating a feasible, safe, and smooth path, thereby supporting the autonomous navigation of UWIGC in island reef waters. Full article

Combine harvesters in lodged, wet, weedy, uneven, or otherwise heterogeneous fields operate under rapidly changing feed rate, load, and material flow conditions. These disturbances often appear as drum overload, cleaning loss, grain breakage, impurity increase, and unstable travel, whereas conventional fixed-parameter operation still depends heavily on operator experience. This review examines intelligent perception and control technologies for combine harvesters from a mechanism-to-control perspective. The discussion covers dynamic load evolution, cleaning loss and grain damage mechanisms, multivariable coupling, pre-harvest perception, feed rate and internal state sensing, result layer loss and quality monitoring, forward speed control, threshing drum load regulation, adaptive cleaning control, and whole machine integration. The literature shows a clear shift from isolated sensing or single-parameter adjustment toward multimodal perception, state estimation, predictive control, digital twins, and edge deployment. At the same time, field robustness, cross-condition generalization, actuator bandwidth, sensing delay, and the coupling between result layer monitoring and closed-loop control remain the main barriers to deployment. The review, therefore, argues for a whole machine architecture that links environmental preview, internal state estimation, loss quality feedback, actuator-aware control, and cloud–edge–device collaboration for stable, low-loss, and autonomous harvesting in complex agricultural environments. Full article

The development of accessible and experimentally validated robotic systems for engineering education is a challenge, especially in academic environments where industrial manipulators are economically inaccessible. This paper presents the design, mechanical validation, and experimental evaluation of a robotic arm-based didactic module developed for the classification of objects according to color and morphology. The proposed system integrates a five-degree-of-freedom articulated configuration, a servomotor drive, motion planning with a trapezoidal speed profile, and a web-based control interface, enabling local and remote operation within an educational environment aligned with Industry 4.0 principles. The mechanical structure was designed using CAD modeling and validated through static structural analysis to ensure mechanical integrity and adequate safety factors. The selection of actuators was made considering the torque, angular velocity, and load requirements. A trapezoidal speed profile was implemented in order to ensure smooth trajectories and minimize positioning errors. Experimental validation was carried out through repetitive tests under controlled laboratory conditions, evaluating the accuracy and repeatability metrics. Statistical indicators such as mean error, standard deviation, and root mean square error (RMSE) were calculated. The results show the stable performance of the system, with low variability in multiple test cycles, confirming the viability of the proposed architecture for its implementation in automation and educational robotics laboratories. The integration of structural validation, motion control strategy, and experimental quantitative evaluation contributes to bridging the gap between theoretical teaching of robotics and its practical application, offering a scalable, low-cost platform for engineering training. Full article

Tail striking is a typical safety event in the area of civil aviation, which is directly related to the aircraft pitch angle at landing. Based on 2933 A319 flights’ non-exceedance quick access recorder (QAR) data from Dali airport, the relationship between key flight parameters during the final approach and landing pitch angle is explored. Functional data analysis and the Group Lasso method are used to select the most important flight parameters, and cluster analysis and weighted logistic regression are used to identify and predict a “high-risk” flight pattern. Here, “high risk” refers to a flight pattern associated with a higher probability of large landing pitch attitude, which is used as a proxy indicator of potential tail-strike risk rather than as evidence of an actual tail-strike event. Finally, flight operation recommendations are provided. The research results indicate that the airspeed, pitch angle and engine speed are most closely related to the landing pitch angle. An unusually high-risk flight pattern is identified, characterized by “high airspeed, high attitude, low thrust” caused by improper energy management of light-load flights. About 32.4% of flights in this pattern land with “large landing attitude”, which means the landing pitch angle is larger than the 95% sample percentile. A prediction model for the high-risk pattern is established using QAR parameters at the heights of 500 ft, 450 ft, and 400 ft, with an accuracy rate of 99.7% on the test data. The prediction in advance at 400 ft can provide pilots with sufficient time to take necessary operations. Full article

In response to the conflicting issues faced by tugboats under different operating conditions, where they simultaneously require “high thrust” while aiming for “low fuel consumption and low thermal load operation”, this paper focuses on the tugboat main engine propulsion system. A multi-objective optimization-based fuel-saving control strategy is proposed. The engine speed and cooling water valve opening are used as control variables, and three performance indicators—the thrust output, fuel consumption rate, and diesel engine operating temperature—are considered comprehensively. A multi-objective optimization mathematical model is established, incorporating the tugboat’s main engine thrust model, fuel consumption model, and engine temperature model. An improved multi-objective genetic algorithm (NSGA-II) is introduced to solve the tugboat fuel consumption optimization problem. Through case analysis, the Pareto optimal solution set for the tugboat’s operating conditions is obtained, revealing the trade-off relationships between the thrust, fuel consumption, and temperature under different control variable combinations. The results indicate that this method provides effective control strategy references for tugboat operation under high thrust, fuel-saving, and balanced economic conditions. It has a certain engineering application value for improving the economic efficiency and the safety of tugboats. Full article

Background/Objectives: The relationship between psychotropic medication use, prescribing appropriateness, and fall-related risk factors remains incompletely characterised. Gait speed is a key predictor of falls. We aimed to examine whether gait speed is associated with appropriately versus inappropriately prescribed psychotropic medication use among relatively healthy older adults. Methods: We conducted an observational cross-sectional study of 119 community-dwelling adults aged ≥ 70 years with low comorbidity burden (Charlson Comorbidity Index < 2) and preserved functional status (Barthel Index > 85). Gait speed was assessed over 6 metres. Psychotropic medication use was recorded and prescribing appropriateness was evaluated using STOPP/START and Beers criteria, supplemented by geriatric pharmacological considerations. Multivariable linear regression analyses adjusted for age, sex, waist-to-height ratio, and frailty status. Results: In the fully adjusted model, inappropriate psychotropic medication use was associated with significantly slower gait speed compared with no use (B = −0.109 m/s; p = 0.026). In contrast, appropriately prescribed psychotropic medication use was not associated with gait speed (B = −0.018 m/s; p = 0.699). Conclusions: In this cross-sectional sample of relatively healthy older adults, appropriate psychotropic medication use was not associated with gait speed impairment, whereas inappropriate use was associated with slower gait. Although causal inference is not supported, these findings may inform prescribing quality and fall-risk assessment in older populations. Full article

Air pollution poses significant risks to public health, ecosystems, and regional economies, particularly in rapidly developing regions. Despite its importance, the Middle East remains relatively understudied in regional air quality, with limited evaluations of pollutant transport and model performance. This study applies the WRF (Weather Research and Forecasting) model coupled with the CAMx (Comprehensive Air Quality Model with Extensions) model to simulate meteorology and air quality over West Asia, with a focus on the United Arab Emirates (UAE). Six representative months are analyzed, including three winter periods (January 2018, 2020, 2022) and three summer periods (June 2017, 2019, 2021). WRF shows good agreement with observations, reproducing near-surface temperature with an index of agreement (IOA) between 0.90 and 1.00 and generally low wind speed (MB < ±0.5 m s⁻¹) and wind direction biases (MB < ±0.5), although cloud-radiative forcing is underestimated during winter. CAMx reproduces PM_2.5 concentrations with moderate-to-high correlations (r = 0.44–0.65) and low bias, while AOD and O₃ column concentration show larger uncertainties. Satellite-based evaluation indicates good performance for NO₂ and CO column abundances but larger discrepancies for HCHO and SO₂, particularly during summer. Overall, the results demonstrate that the WRF-CAMx modeling system provides a reliable framework for regional air quality simulations over West Asia, while highlighting uncertainties associated with emissions, atmospheric chemistry, and satellite retrieval products. Full article

Precise segmentation of weld defects offers clearer advantages over simple localization in the modern manufacturing, which can improve reliability in high-density weld zones. In order to improve the segmentation mean Average Precision (mAP) and inference speed, we propose a hybrid WFD-YOLO that employs a wavelet-based frequency down-sampling (WFD) module, a lightweight channel-thresholding attention (CTA), and a dedicated P2 small-object layer for weld defect segmentation, where the WFD module is used for suppressing aliasing while preserving low-frequency structural details, the CTA module is used for reducing the impact of background and noise during defect segmentation, and the dedicated P2 small-object layer is used for giving explicit sensitivity to minor defects like porosity and spatters. The upgraded model improves precision by 3.5%, recall by 7.8%, mAP@0.5 by 7.3%, and mAP@0.5–0.95 by 2.7% over the original YOLO11n-seg, while achieving an inference speed of 303 FPS. The segmentation mAP for porosity and spatters, which represent the most challenging defect categories, is improved by 16% and 15.8%, respectively. These performance gains position the hybrid WFD-YOLO network as an industry-deployable tool for safety-critical weld inspection, compatible with high-speed automated welding production lines. Full article

Next-generation unmanned aerial vehicles require compact propulsion systems capable of providing efficient vertical lift, rapid thrust vectoring, and improved maneuverability. Cyclorotors represent a promising alternative to conventional propellers, but their aerodynamic behavior is governed by highly unsteady blade–wake interactions, making performance prediction challenging. This study investigates a four-bladed cyclorotor equipped with NACA 0012 airfoils using transient computational fluid dynamics simulations and a calibrated semi-analytical blade-element model. The numerical analysis was performed over a rotational-speed range of 368–2305 rpm and for several pitch-amplitude configurations, including 5°, 7.5°, 10°, 12.5° and 15°. The results showed that the favorable pitch amplitude decreases with increasing rotational speed, shifting from larger amplitudes at low RPM to approximately 5° at higher RPM values. The semi-analytical model reproduced the main CFD trends for lift, drag, moment, and power, providing a reduced-order tool for preliminary cyclorotor performance estimation. The comparison confirmed that pitch-amplitude selection strongly influences aerodynamic loading and efficiency and should therefore be adapted to the operating regime. The proposed CFD-based methodology, supported by semi-analytical modelling, provides a useful framework for the aerodynamic characterization and early-stage optimization of cyclorotor propulsion systems for UAV applications. Full article

This study proposes a canopy-adaptive TAD-IRRT* (target-biased sampling, artificial potential field, and dynamic step-size informed rapidly-exploring random tree star) algorithm to solve the collision-free 3D path-planning problem for a 6-DOF apple-harvesting robotic arm. To improve computational speed and search directionality, the method integrates target-biased sampling and a distance-regulated artificial potential field (APF) into the Informed-RRT* framework. Furthermore, an obstacle-distance-based dynamic step-size mechanism is introduced to optimize spatial exploration. The generated routes undergo greedy path pruning and cubic B-spline smoothing to ensure kinematic executability. The simulation results in complicated ROS-based scenarios demonstrate that the TAD-IRRT* algorithm achieves a 100% planning success rate, reducing the average computational time and joint-space path length by approximately 60.1% and 15.6%, respectively, compared to the standard Informed-RRT*. Kinematic analysis via Fourier curve fitting ($R^2=0.9849$) confirms continuous angular velocity and acceleration without high-frequency chattering. Physical prototype experiments in the dense-obstacle scenarios show that the proposed method increases the path execution success rate by 36.7% and reduces the average execution time by 41% compared to the standard Informed-RRT* algorithm. The proposed approach effectively balances high-quality path generation with low computational overhead, providing a reliable and safe solution that significantly reduces mechanical wear. Full article

In order to study the optimal size and sealing performance of the foot-shaped slip ring for reciprocating seal, the loading method of fluid pressure penetration is used to simulate the effect of fluid medium pressure on the seal, and the multi-objective optimization of the geometry of the slip ring is carried out based on optimization software to obtain the best combination of parameters for the foot-shaped slip ring. The effects of slip ring geometry, pre-compression and working pressure on Von Mises stress and contact pressure were investigated using the finite element method. The results show that the optimized geometry of the foot-shaped slip ring can reduce the maximum contact stress on the main sealing surface from 108.5 MPa to 75.22 MPa (a reduction of 30.7%) and decrease the maximum Von Mises stress of the slip ring from 62.84 MPa to 41.57 MPa (a reduction of 33.8%), thereby greatly reducing the wear of the slip ring while ensuring reliable sealing. In the static sealing condition, a smaller pre-compression (1.2–1.3 mm) leads to stress concentration in the O-ring, and the recommended pre-compression range is 1.4–1.6 mm. In the dynamic sealing condition, the effect of pre-compression on the sealing performance is greater than that of reciprocating motion speed on the sealing performance, and the foot-shaped slip ring seal is found to be more suitable for low-speed operation at 0.1–0.2 m/s. The optimized design provides a data-driven methodology for enhancing the reliability and service life of reciprocating seals in high-pressure environments. Full article

Tomato is one of Thailand’s most significant economic crops, generating substantial export value and serving as a primary source of income for local farmers. However, the traditional manual grading process often fails to comply with the Thai Agricultural Standard TACFS 1503–2007, as grading decisions rely heavily on individual experience and subjective perception, resulting in inconsistent quality. Existing automated systems face the challenges of low accuracy, high costs, and complex hardware, while many are incompatible with Thailand’s grading standards. This study presents a multi-view tomato grading system (MVT-Grader), utilizing a dataset acquired from Doi Kham Food Products Co., Ltd. (Third Royal Factory, Tao Ngoi) under controlled lighting conditions. Subsequently, MVT-Grader is built on a custom-designed lightweight CNN architecture with an adjusted spatially aware loss function to enhance the model’s sensitivity in detecting subtle surface defects and color variations. The proposed model was trained using tomato images captured from two and three different viewpoints via a low-cost webcam setup and processed by a GPU-embedded system. Experiments conducted using stratified 5-fold cross-validation on a real-world industrial dataset demonstrate average grading accuracies of 99.43% (two-view) and 99.64% (three-view). Furthermore, the proposed Real-Time Lightweight CNN with Spatially Aware Loss Optimization achieves processing speeds of 87 ms and 114 ms per tomato for two- and three-view cases, respectively. Compared with MVCNN-Siamese, SDF-ConvNets, and Multi-View Spatial Network, the proposed system outperforms the others in both accuracy and speed, improving accuracy by 1.6–6.11% and reducing processing time by 39–49 ms. Full article

Urban Unmanned Aerial Vehicle (UAV) logistics operations are frequently constrained by the intersection of limited battery endurance and dynamic ground traffic. When mobile depots are delayed by congestion, onboard drone fleets experience extended idling periods, leading to constrained sortie generation and reduced asset utilization. To address this bottleneck, this paper introduces a traffic-predictive multi-UAV dispatch framework for deterministic day-ahead planning under modeled urban operating conditions. By coupling a count-derived macroscopic speed surrogate learned using XGBoost with a Particle Swarm Optimization (PSO)–Mixed-Integer Linear Programming (MILP) optimization architecture, the framework synchronizes mobile depot trajectories with forecasted low-congestion windows and pre-allocates endurance-feasible parallel aerial sorties. Controlled computational experiments across 30 synthetic routing instances demonstrate the potential value of this approach within the stated modeling assumptions. Compared to baseline clustered deployments, the traffic-aware framework raises mean fleet utilization from 0.43 to 0.63—a 46.2% relative improvement driven by temporal compression of the mission window rather than an absolute increase in flight hours. Furthermore, the proposed framework reduces total mission completion time by 69.87% relative to the conventional truck-only baseline, while achieving a 29.58% incremental gain over static speed drone deployments. These findings suggest that incorporating predictive ground traffic information into day-ahead UAV scheduling can improve modeled fleet efficiency; however, field validation with measured route-level speeds, real delivery demand, and operational constraints remains necessary before deployment-level claims can be made. Full article

Aiming at the deterioration in Noise, Vibration and Harshness (NVH) performance caused by broadband torsional vibration in the integrated electric drive system (IEDS) of electric vehicles, most existing studies independently focus on electromagnetic excitation suppression or torsional vibration control of mechanical transmissions. Few researchers consider the coupling characteristics between the electromagnetic nonlinearity of motors and the nonlinearity of gear transmissions, making it difficult to realize the coordinated suppression of high- and low-frequency torsional vibration. In this paper, a seven-degree-of-freedom electromechanical coupling dynamic model is firstly established, which incorporates the electromagnetic torque ripple of the motor, the time-varying meshing stiffness of gears, meshing errors, and gear backlash nonlinearity. Through modal analysis and Campbell diagram solution, the natural characteristics and critical speed range of the system are clarified, and the generation mechanism of full-frequency band torsional vibration as well as the high–low frequency coupling characteristics are systematically revealed. On this basis, a coordinated active control strategy based on PD pole placement and harmonic current injection (PD-HCI) is proposed. The PD pole placement controller is adopted to suppress the low-frequency torsional vibration (0–20 Hz) of the transmission system, and the 5th/7th harmonic current injection is used to counteract the high-frequency torque ripple (above 200 Hz) of the motor, thereby achieving the coordinated suppression of broadband torsional vibration. The Matlab/Simulink R2023a simulation results show that the proposed control strategy reduces the torque fluctuation rate from 3.11% to 1.96%, the speed fluctuation rate from 0.10% to 0.03%, and the total harmonic distortion (THD) of stator current from 8.69% to 1.77% under steady-state operating conditions. Under transient operating conditions with sudden load changes, the stabilization time of fluctuations in speed and half-shaft torque is shortened by more than 80%, the impact amplitude is significantly reduced, and there is no loss in the vehicle’s dynamic response and speed tracking performance. Experimental results show that the coefficients of determination R2 of vehicle speed, motor speed, acceleration and torque are 0.9990, 0.9982, 0.9997 and 0.9997, respectively, which verifies the reliability of the established model. Full article

This study examined how duct inclination influences particle removal in a hybrid acoustic–electrostatic filtration system operating at low airflow velocities. The experiments were carried out in a 150 mm diameter air duct at airflow speeds of 0.50 and 0.75 m/s, with duct inclinations of 45° and 90°. Aerosol particles with properties similar to marine diesel exhaust, spanning a size range of 0.2–10 µm, were introduced at stable concentrations. Electrostatic voltages of 17.5 and 20 kV were applied, together with acoustic voltages between 100 and 200 V. Particle removal was evaluated using both size-resolved and overall collection efficiencies. The results show that duct inclination mainly affects the removal of fine and medium-sized particles. The largest differences were observed for particles around 1 µm in diameter, where the vertical duct increased collection efficiency by up to 27 percentage points at an airflow speed of 0.75 m/s. For larger particles in the 5–10 µm size range, high removal efficiency was achieved under all tested conditions, and duct orientation had a smaller influence on collection performance. Overall, the results confirm that duct inclination has a clear and measurable effect on the performance of hybrid acoustic–electrostatic filtration systems operating at low airflow velocities. Full article