Search Results (378)

This study aims to develop and demonstrate a low-cost LiDAR-based 3D mapping approach for estimating tree carbon stock in university campuses. Unlike conventional field-based measurements, which are labor-intensive and error-prone, the proposed system integrates a 2D LiDAR sensor with a servo motor and odometry data to generate three-dimensional point clouds of trees. From these data, key biometric parameters such as diameter at breast height (DBH) and total height are automatically extracted and incorporated into species-specific and generalized allometric equations, in line with IPCC 2006/2019 guidelines, to estimate above-ground biomass, below-ground biomass, and total carbon storage. The experimental study is conducted over approximately 70,000 m² of green space at Gazi University, Ankara, where six dominant species have been identified, including Cedrus libani, Pinus nigra, Platanus orientalis, and Ailanthus altissima. Results revealed a total carbon stock of 16.82 t C, corresponding to 61.66 t CO₂eq. Among species, Cedrus libani (29,468.86 kg C) and Ailanthus altissima (13,544.83 kg C) showed the highest contributions, while Picea orientalis accounted for the lowest. The findings confirm that the proposed system offers a reliable, portable, cost-effective alternative to professional LiDAR scanners. This approach supports sustainable campus management and highlights the broader applicability of low-cost LiDAR technologies for urban carbon accounting and climate change mitigation strategies. Full article

The accuracy of dynamics parameters in the transmission system is essential for high-performance motion trajectory planning and stable operation of heavy-duty servo presses. To mitigate the performance degradation and potential overload risks caused by deviations between theoretical and actual parameters, this paper proposes a dynamics model accuracy enhancement method that integrates multi-objective global sensitivity analysis and ant colony optimization-based calibration. First, a nonlinear dynamics model of the eight-bar mechanism was constructed based on Lagrange’s equations, which systematically incorporates generalized external force models consistent with actual production, including gravity, friction, balance force, and stamping process load. Subsequently, six key sensitive parameters were identified from 28 system parameters using Sobol global sensitivity analysis, with response functions defined for torque prediction accuracy, transient overload risk, thermal load, and work done. Based on the sensitivity results, a parameter calibration model was formulated to minimize torque prediction error and transient overload risk, and solved by the ant colony algorithm. Experimental validation showed that, after calibration, the root mean square error between predicted and measured torque decreased significantly from 1366.9 N·m to 277.7 N·m (a reduction of 79.7%), the peak error dropped by 72.7%, and the servo motor’s effective torque prediction error was reduced from 7.6% to 1.4%. In an automotive door panel stamping application on a 25,000 kN heavy-duty servo press, the production rate increased from 11.4 to 11.6 strokes per minute, demonstrating enhanced performance without operational safety. This study provides a theoretical foundation and an effective engineering solution for high-precision modeling and performance optimization of heavy-duty servo presses. Full article

Permanent Magnet Synchronous Motors (PMSMs) are central to high-performance servo drives, yet their control accuracy is often compromised by parameter uncertainties and external disturbances. While the Uncertainty and Disturbance Estimator (UDE) offers enhanced robustness by treating such uncertainties as lumped disturbances, it suffers from significant integral windup under output saturation, degrading dynamic response. This paper proposes a symmetry-principle-based UDE control strategy for the PMSM speed loop, which simplifies parameter tuning through derived analytical expressions for PI gains. To address the windup issue, two anti-windup algorithms are introduced and critically compared: a piecewise tracking back-calculation method and an integral final value prediction algorithm. The key finding is that the integral final value prediction algorithm demonstrates a superior performance. Simulation results show that it reduces the convergence time by 6.3 ms and the overshoot by 1.8% compared to the piecewise method. Experimental validation on an STM32F446-based platform confirms these findings. Under a 600 r/min step with load, the UDE controller with the integral final value prediction algorithm reduces speed overshoot by 15% compared to the piecewise algorithm and by 47% compared to the standard UDE controller without anti-windup. These results conclusively show that the proposed integrated strategy—combining symmetry-based UDE control with the integral final value prediction anti-windup algorithm—significantly improves the dynamic response, accuracy, and robustness of PMSM servo systems. Full article

The tailless flapping-wing micro aerial vehicle (FW-MAV) exhibits capabilities for hovering and agile six-degree-of-freedom flight, demonstrating potential for missions in complex environments such as forests and indoor spaces. However, limited payload and endurance restrict their practical application. This study presents a novel tailless FW-MAV named X-fly, incorporating a lightweight crank-rocker mechanism with high thrust-to-weight ratio. The optimized flapping-wing mechanism achieves a maximum single-side lift of 28.7 gf, with a lift-to-power ratio of 6.67 gf/W, outperforming conventional direct-drive propellers using the same motor. The X-fly employs servo-controlled stroke planes for tailless attitude stabilization and rapid disturbance recovery. It features a 36 cm wingspan and a net weight of 18.9 g (without battery). Using a commercially available 1100 mAh battery weighing 21.6 g, it demonstrates a peak lift-to-weight ratio of 1.42 at 3.8 V and achieves a maximum flight endurance of 33.2 min. When equipped with a 250 mAh battery weighing 5.5 g, it can carry an additional payload equal to its own net weight. The X-fly attains a maximum speed of 6 m/s and demonstrates high agility during forest flight. Furthermore, it successfully performs a simulated reconnaissance mission with an onboard camera, confirming its potential for practical applications. Full article

Reliable positioning performance is crucial in precision industrial automation, especially under dynamic conditions. This research focuses on examining the accuracy of a toothed belt driven linear servo motor positioning system, with the aim of identifying the main factors influencing position deviation. The system was built on a Power Belt ITO 060M shaft, controlled by an Rtelligent RS200-G servo controller and an Omron CP1L-E PLC. Position measurement was performed by a laser distance meter and a Cognex IS2000C-130-40-SR8 industrial camera, both calibrated with certified gauge blocks. The linear unit was moved to predefined points at different speeds, accelerations, and decelerations profiles and the resulting position deviation was recorded for each case. Several analytical methods were used to evaluate the collected measurement data to determine which factors have the greatest impact on positioning error. The result showed that speed significantly affected the accuracy of the system, while the effects of deceleration and acceleration were less pronounced. The study contributes to the fine-tuning of linear motion system and the targeted improvement of their performance. Full article

Seismic metamaterial-inspired periodic foundations have emerged as promising vibration-mitigation concepts capable of attenuating seismic wave propagation within specific frequency bands. This study presents an experimental investigation on the dynamic response of periodic foundation configurations, with and without embedded piezoelectric layers, to evaluate their vibration-attenuation characteristics. The experimental program employed a shake table driven by a 0.75 kW servo motor and included excitation step counts of 3000, 4000, and 5000. Accelerometers mounted on the specimen surfaces recorded vibration data at 80 ms intervals. Three foundation configurations were tested: (i) a conventional reinforced concrete block, (ii) a one-dimensional periodic foundation composed of alternating concrete and rubber layers, and (iii) a periodic foundation incorporating piezoelectric modules. Time-domain and frequency-domain analyses showed that the periodic foundations achieved notable reductions in both peak and RMS accelerations, especially near resonance frequencies. The configuration, including piezoelectric layers, exhibited similar attenuation performance while also generating measurable instantaneous voltage outputs under vibration. However, these voltage peaks—reaching a maximum of 1.64 V—represent only a laboratory-scale, proof-of-concept demonstration of electromechanical coupling rather than a practical or continuous form of energy harvesting, given the inherently sporadic nature of seismic excitation. Overall, the results confirm that the tested system is not a full metamaterial in the classical sense but rather a metamaterial-inspired periodic arrangement capable of inducing band-gap-based vibration attenuation. The inclusion of piezoelectric elements provides auxiliary sensing and micro-energy-generation capabilities, offering a preliminary foundation for future multifunctional seismic-protection concepts. Full article

This paper presents an approach to the velocity control loop of induction motor drives utilizing the Higher-Order PID-Nested Nonsingular Terminal Sliding Mode (PID-NTSM) method. Here, the PID-NTSM sliding manifold is formulated by the incorporation of both derivative and integral errors of states into the conventional nonsingular terminal sliding mode surface (NTSM). In this manner, the control signals take the higher-order sliding mode control law, obtained by multiple integrals. In this way, such signals are continuous, and the sliding manifold is obtained in finite time; the system’s states asymptotically converge chattering-free to zero at a much faster response time and higher tracking precision while maintaining inherited robustness characteristics. The effectiveness of the proposed method is comprehensively validated both numerically and experimentally. Full article

The electric spindle serves as a critical component in enabling a highly dynamic response, stable torque output, and precise motion control for the main cutting operations of CNC machine tools. The design precision and control performance of its drive motor directly influence the geometric accuracy, surface quality, and overall machining efficiency of the workpiece, thereby determining the comprehensive performance of advanced CNC systems. This paper begins with a systematic review of the global industrial layout of CNC machine tool and electric spindle manufacturers, highlighting regional clustering patterns and technological development trends across key manufacturing regions. Subsequently, it classifies and elaborates on the differentiated technical requirements for the electric spindle motor in terms of wide-speed-range servo capability, high-efficiency operation, adaptability to high-speed and high-power cutting loads, and precision maintenance under high-speed conditions, based on the process characteristics of different types of CNC machine tools. A comprehensive overview of the current state of research is provided with respect to electric spindle motor design and control technologies. Finally, forward-looking perspectives are presented on future development directions, particularly in the areas of multi-physics coupling co-design and the integration of intelligent control algorithms, aiming to offer a solid theoretical foundation and strategic guidance for the advancement and engineering application of high-performance electric spindles. Full article

Electro-hydraulic servo fatigue testing machines are susceptible to concurrent degradation and failure of multiple components during high-frequency, high-load, and long-duration cyclic operations, posing significant challenges for online health monitoring. To address this, this paper proposes a multi-state recognition method based on spatiotemporal feature fusion and bidirectional cross-attention. The method employs a Bidirectional Temporal Convolutional Network (BiTCN) to extract multi-scale local features, a Bidirectional Gated Recurrent Unit (BiGRU) to capture forward and backward temporal dependencies, and Bidirectional Cross-Attention (BiCrossAttention) to achieve fine-grained bidirectional interaction and fusion of spatial and temporal features. During training, GradNorm is introduced to dynamically balance task weights and mitigate gradient conflicts. Experimental validation was conducted using a real-world multi-sensor dataset collected from an SDZ0100 electro-hydraulic servo fatigue testing machine. The results show that on the validation set, the cooler and servo valve achieved both accuracy and F1-scores of 100%, the motor-pump unit achieved an accuracy of 98.32% and an F1-score of 97.72%, and the servo actuator achieved an accuracy of 96.39% and an F1-score of 95.83%. Compared to single-task models with the same backbone, multi-task learning improved performance by approximately 3% to 4% for the hydraulic pump and servo actuator tasks, while significantly reducing overall deployment resources. Compared to single-task baselines, multi-task learning improves performance by 3–4% while reducing deployment parameters by 75%. Ablation studies further confirmed the critical contributions of the bidirectional structure and individual components, as well as the effectiveness of GradNorm in multi-task learning for testing machines, achieving an average F1-score of 98.38%. The method also demonstrated strong robustness under varying learning rates and resampling conditions. Compared to various deep learning and fusion baseline methods, the proposed approach achieved optimal performance in most tasks. This study provides an effective technical solution for high-precision, lightweight, and robust online health monitoring of electro-hydraulic servo fatigue testing machines under complex operating conditions. Full article

Vehicle axle load scales are one of the most important devices for vehicle safety testing. To ensure the stability and reliability of test results, regular calibration of axle load scales is necessary. Traditional calibration methods are inefficient and error-prone. In this work, an automatic calibration device for portable axle load scales was presented, which uses a pump-controlled hydraulic cylinder as a loading unit. The loading unit was controlled by a high-precision force sensor and a PLC. A hydraulic unit based on a servo motor and a gear pump was designed, and control software including automatic control, data acquisition, and report generation was developed. The experimental test was carried out. The results showed that the developed portable automatic calibration device could realize the automatic calibration of a 0~150 kN load range, and the accuracy level was up to ±0.3%. Finally, it was verified that the device had the advantages of compactness and lightweight and simple operation. Full article

This paper presents a comprehensive modeling and control strategy for a pan–tilt (PT) servo system designed for real-time object tracking (specifically face detection) using deep learning and PID control. The system integrates a YOLO-based neural network to detect and localize the target within an image, mapping its coordinates from 3D space onto the 2D image plane through a mathematically defined geometric camera model. A complete mathematical representation of the pan–tilt mechanism is developed, accounting for all relevant forces and system components. Based on this model, a PID controller is designed, and its parameters are identified and implemented using the Ziegler–Nichols tuning method. Experimental results demonstrate that the system effectively tracks objects in real time, exhibiting minimal latency and precise motor responses. These findings suggest that the proposed approach is well-suited for practical applications, including security surveillance, assistive technologies, and interactive robotics. Full article

Upper limb disabilities resulting from stroke affect millions worldwide, yet current rehabilitation systems face limitations in portability, cost-effectiveness, and multi-joint integration. This study presents a cable-driven parallel exoskeleton integrating elbow, wrist, and finger assistance into a single portable device. The design strategically separates actuation components, housing all motors in a backpack unit, while limb-mounted modules serve as cable routing guides, achieving seven degrees of freedom within practical constraints of portability (1.2–1.5 kg) and cost-effectiveness (3D-printed components). The device incorporates seven servo motors controlled via Arduino with IMU feedback and PID algorithms. Kinematic and dynamic analyses informed mechanical design, while ARMAX system identification enabled controller optimization achieving 87.96% model fit. Experimental validation with eight healthy participants performing four upper limb exercises demonstrated consistent trends toward reduced activation in four monitored agonist muscles with exoskeleton assistance (21.3% average reduction, p = 0.087), with moderate effect sizes for proximal muscles (Cohen’s d = 0.70–0.79) and significant reductions in brachioradialis during radial/ulnar deviation (23.4%, p = 0.045). These findings provide preliminary evidence of the device’s potential to reduce muscular effort during assisted movements, warranting further clinical validation with patient populations. Full article

The electrification of non-road mobile machinery is advancing to enhance sustainability and reduce emissions. This study investigates how to maximize the efficiency of the retrofitting of a material handler from an internal combustion engine to a battery-powered electric motor, while keeping the hydraulic system unchanged. Using a previously validated model, this study proposes three control strategies for the electric motor and hydraulic pump to enhance efficiency and performance. The first control strategy optimizes hydraulic pump performance within its most efficient displacement range. The second strategy maximizes powertrain efficiency by considering both efficiencies of the electric motor and hydraulic pump. The third strategy uses a servo-actuated valve to adjust the load-sensing margin and exhibits energy savings up to 14.2% and an 11.5% increase in efficiency. The proposed strategies avoid complex optimization algorithms, ensuring practical applicability for small- and medium-sized enterprises, which often face cost constraints and limited scalability. Full article

Permanent Magnet Synchronous Motors (PMSMs) have been widely applied across various electrical systems due to their significant advantages, including high power density, high-efficiency conversion, and easy controllability. However, the issue of ‘parameter asymmetry’ (a mismatch between the controller’s preset parameters and the actual system parameters) in PMSMs can lead to performance problems, such as delayed speed response and increased overshoot. The destruction of symmetry, including the asymmetric weight distribution between new and old data in the moment-of-inertia identification algorithm and the asymmetry between “measured values and true values” caused by sampling delay, is the core factor limiting the system’s control performance. All these factors significantly affect the accuracy of parameter identification and the system’s stability. To address this, this study focuses on the mechanical parameter identification of PMSMs with the core goal of “symmetric matching between set values and true values”. Firstly, a current-speed dual closed-loop vector control system model is constructed. The PI parameters are tuned to meet the symmetric tracking requirements of “set value-feedback” in the dual loops, and the influence of the PMSM’s moment of inertia on the loop symmetry is analyzed. Secondly, the symmetry defects of traditional algorithms are highlighted, such as the imbalance between “data weight and working condition characteristics” in the least-squares method and the mismatch between “set inertia and true inertia” caused by data saturation. Finally, a Forgetting Factor Recursive Least Squares (FFRLS) scheme is proposed: the timing asymmetry of signals is corrected via a first-order inertial link, a forgetting factor λ is introduced to balance data weights, and a recursive structure is adopted to avoid data saturation. Simulation results show that when λ = 0.92, the identification accuracy reaches +5% with a convergence time of 0.39 s. Moreover, dynamic symmetry can still be maintained under multiple multiples of inertia, thereby improving identification performance and ensuring symmetry in servo control. Full article

In pharmaceutical and biomedical industries, manual handling of dangerous chemicals is a leading cause of hazardous exposure to chemicals, toxic burning, and chemical contamination. To counteract these risks, we proposed a gesture-controlled bionic hand system to mimic human finger movements for safe and contactless chemical handling. This innovation system uses an ESP32 microcontroller to decode the hand gestures that are detected by the system using computer vision via an integrated camera. A PWM servo driver converts these movements to motor commands such that accurate movements of the fingers can be achieved. Teflon and other corrosion-proof materials are utilized in the 3D printing of the bionic hand in order to withstand corrosive conditions. This new, low-cost, and non-surgical approach replaces the EMG sensors, gives real-time control, and enhances industrial and laboratory process safety. The project is a major milestone in the application of robotics and AI for automation and risk reduction in dangerous environments. Full article