Gearboxes used in the drivetrain of intelligent robots are key mechanical components that play a significant role in determining the performance of modern robotic systems. Gearboxes employing the planetary gear mechanism, known to achieve a wide range of reduction ratios while remaining relatively cost-effective, have recently been adopted in robot drivetrains. In this paper, we utilize domestic technology to fabricate a gearbox using a compound planetary gear mechanism and conduct an evaluation of eight performance aspects of the developed gearbox through the fabrication of a dynamometer and a jig. The dynamometer comprised of the gearbox, input motor, input-output torque sensors, and a powder brake. By driving the input motor and applying braking force with the powder brake, we compare input torque sensor values with output torque sensor values to derive results. A test jig is created, consisting of an input motor, gearbox, and encoder sensor, for the measurement of inverse operation characteristics and backlash. By conducting a performance evaluation of the developed high-strength, high-reduction-ratio compact planetary gearbox, we validate the potential of the testing system and extend the scope of domestic gearbox technology development.
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Three-dimensional reconstruction of gearbox from multi-view point clouds with surface feature parfameter measurement method Jian Chen, Zhijia Zhang, Guanghui Liu, Dejian Li, Qiushuang Li Engineering Research Express.2025; 7(4): 045253. CrossRef
The pneumatic vibration isolator is economical, has no risk of contamination, and attains high vibration isolation performance by lowering the natural frequency. Pressure feedback control is used to improve the response speed of the pneumatic vibration isolator and keep the internal pressure of the pneumatic actuator constant. In this paper, the vibration isolator was actively controlled by estimating the internal pressure of the pneumatic actuator with the displacement signal. A pneumatic actuator was modeled and its dynamic characteristics were identified through frequency response measurements. A pressure observer based on relative displacement was designed, and the observer control gain was adjusted with nominal model and experiments. Pressure estimation performance and active vibration suppression performance using a pressure observer were verified through experiments. The pressure of the pneumatic actuator was estimated by the observer, and measurement noise was eliminated effectively. In addition, vibration isolation performances of direct and estimated pressure feedback showed no difference, verifying the effectiveness of the pressure observer.
This study investigated the influence of cooling rate and Sn addition on the microstructure formation of as-cast GCD700 spheroidal graphite cast irons. Changes in cooling rate manifested as step cast thickness differences. Optical microstructures of as-cast GCD700 alloys revealed α-ferrite and pearlite and dispersed graphite nodules. In all examined thicknesses without Sn, the α-ferrite, rather than the pearlite, surrounding graphite nodules appeared to dominate microstructures, and the graphite looked well rounded, whereas microstructure containing 0.09% Sn had a significantly expanded pearlite area. Image analysis showed numbers of graphite nodules increased only on decreasing cast thickness. However, the phase fractions of ferrite and pearlite were not dependent on thickness. For samples containing Sn, pearlite fractions significantly increased with Sn content. Thermodynamic calculations and scanning electron microscopy-based microstructural analysis confirmed that the Sn contents examined had no significant effect on phase formation, Sn segregation, or the relationships between ferrite and Fe3C orientations in pearlite.
The elastic property of a copper (Cu) thin film was investigated using the surface acoustic wave (SAW) measurement technique. The Cu film was deposited on a quartz substrate using a direct current magnetron sputter and its surface morphology was inspected using atomic force microscopy. Time-domain waveforms of the SAW on the film were acquired at different propagation distances to estimate the Young’s modulus of Cu such that the experimentally-obtained dispersion curve can be compared to the analytical result calculated using the Transfer Matrix method for curve-fitting. Results showed that the film’s elastic property value decreased by 18.5% compared to that of the bulk state, and the scale effect was not significant in the thickness range of 150-300 nm, showing good agreement with those by the nanoindentation technique. The property, however, increased by 15.5% with the grain coarsening.
Estimating energy expenditure is essential in monitoring the intensity of physical activity and health status. Energy expenditure can be estimated based on wearable sensors such as inertial measurement unit (IMU). While a variety of methods have been developed to estimate energy expenditure during day-to-day activities, their performances have not been thoroughly evaluated under walking conditions according to various speeds and inclines. This study investigated IMU-based neural network models for energy expenditure estimation under various walking conditions and comparatively analyzed their performances in terms of sensor attachment locations and training/testing datasets. In this study, two neural network models were selected based on a previous study (Slade et al., 2019): (M1) a multilayer perceptron using sensor signals during each gait cycle, and (M2) a recurrent neural network using sensor signal sequences of a fixed window size. The results revealed the following: (i) the performance of the foot attachment model was the best among the five sensor attachment locations (0.89 W/kg for M1 and 1.14 W/kg for M2); and (ii) although the performance of M1 was superior to that of M2, M1 requires accurate gait detection for data segmentation by each stride, which hinders the usefulness of M2.
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Development of a Novel Ventilation Estimation Model Based on Convolutional Neural Network (CNN) Jeongyeon Chu, Jaehyon Baik, Kangsu Jeong, Seungwon Jung, Youngjin Park, Hosu Lee Journal of Korea Robotics Society.2025; 20(1): 138. CrossRef
During its early development stages, 3D printing was primarily used for rapid prototyping, whereas it is currently employed to fabricate products in various fields, including aerospace, automobile production, dentistry, architecture, and food. The photopolymerization of the polymer used for 3D printing is precise and provides excellent surface roughness but has lower mechanical strength than traditional manufacturing methods. In this study, Multi-walled Carbon Nanotubes (MWCNTs) were blended with urethane acrylate-based resin as a filler. Mechanical strength enhancement was confirmed using a DLP 3D printer. The stabilities of MWCNT dispersions in resin were verified, and viscosity and curing depth measurements were conducted to establish 3D printing parameters. Tensile and flexural strengths were higher for an MWCNT length of 50 μm than one of 100 μm, and maximum values were obtained at an MWCNT content of 0.1 phr. Under optimal conditions, tensile and flexural strengths increased by 2.1 and 1.8-fold, respectively.
The Glass Molding Process (GMP) produces large quantities of glass optical parts and provides the advantages of high molding accuracy, short production cycle, low cost, and little pollution. Developments in different sectors, such as cameras and telescopes, are prompting studies on the design of aspherical optical components. Modeling heat transfer and deformation at high temperatures are crucial aspects of studying glass because its properties are significantly influenced by temperature-induced phase changes. In this study, temperature changes and geometric deviations of lenses were studied with respect to heating, pressing, and cooling times and the heat capacity of the heater used. A 3D model was designed for the heating, pressing, and cooling steps, and heat transfer was subjected to numerical analysis considering the specific heat of glass and the temperature dependence of thermal conductivity. Lens molding temperature conditions were then analyzed with the heat capacity of the lens molding heating system. Lens molding conditions were derived by analyzing lens temperatures with respect to heating and cooling capacities at each process step.
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Precision glass aspherical lens manufacturing by compression molding: a review Xiaohua Liu, Jian Zhou, Bo Tao, Yang Shu, Zexin Feng, Shih-Chi Chen, Yingying Zhang, Allen Y. Yi Light: Advanced Manufacturing.2026; 7: 1. CrossRef
A Study on Temperature and Stress Distribution in a Lens under Multi-Stage Cooling Conditions in Progressive Glass Molding Processes Ji Hyun Hong, Jeong Taek Hong, Dong Yean Jung, Young Bok Kim, Keun Park, Chang Yong Park Journal of the Korean Society for Precision Engineering.2025; 42(2): 157. CrossRef
The Ball-on-Plate Balancing System is a system where the base is fixed to the ground, and the plate is connected to the base through a spherical joint and can rotate in two directions (X-axis roll rotation, Y-axis pitch rotation). Two rotational joints are located on the orthogonal coordinate line of the base, and these joints are connected to the operational links of a 4-bar linkage, creating rotation of the plate around the spherical joint. The goal of this system is to prevent a ball placed on the plate from rolling off and maintain it at the center of the plate. A 17-inch touch panel attached to the plate allows the orthogonal coordinates of a ball placed on the plate to be measured. A cross-shaped frame was designed to secure the touch panel, and a custom universal joint was centered in this frame. The Ball-on-Plate Balancing System was integrated into a cart table, and a horizontal maintenance system was designed to keep the table level. Experiments confirmed the ability of the table to maintain its horizontal position during movements on uneven surfaces and sudden starts or stops.
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Design of a Controller to Overcome Air Ball in the Ball-on-plate System Applied to a Shelf Cart Sangsin Park Journal of the Korean Society for Precision Engineering.2025; 42(4): 301. CrossRef
In recent years, research on machine learning techniques that can be integrated with existing suspension control algorithms for enhanced control effects has advanced considerably. Machine learning, especially involving neural networks, often requires many samples, which makes maintaining robust performance in diverse, changing environments challenging. The present study applied reinforcement learning, which can generalize complex situations not previously encountered, to overcome this obstacle and is crucial for suspension control under varying road conditions. The effectiveness of the proposed control method was evaluated on different road conditions using the quarter-vehicle model. The impact of training data was assessed by comparing models trained under two distinct road conditions. In addition, a validation exercise on the performance of the control method that utilizes reinforcement learning demonstrated its potential for enhancing the adaptability and efficiency of suspension systems under various road conditions.
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Control Characteristics of Active Suspension in Vehicles using Adaptive Control Algorithm Jeong Seo Jang, Jung Woo Sohn Transactions of the Korean Society for Noise and Vibration Engineering.2024; 34(5): 568. CrossRef
Suspension Mechanism Design of a Low-platform Target Robot for Evaluating Autonomous Vehicle Active Safety Jae Sang Yoo, Do Hyeon Kim, Jayil Jeong Journal of the Korean Society for Precision Engineering.2024; 41(5): 375. CrossRef
Rolling bearing fatigue life is an essential criterion in industrial equipment design and manufacturing and requires precise maintenance and replacement predictions. ISO/TS 281:2007 and 16281:2008 are commonly used for angular contact ball bearing (ACBB) fatigue life calculations, but they do not account for the characteristics of individual bearing elements under combined loading conditions. This study proposes an enhanced formula for calculating fatigue life modification factors that considers individual element-specific contact loads and resulting film thickness variations. The proposed fatigue life formula provides longer life predictions than the conventional method of determining modification factors based solely on maximum contact loads. This difference is particularly noticeable in low-speed and/or heavy-loading applications. Analysis conducted using the proposed fatigue life formula on various factors affecting fatigue life revealed that fluid kinetic viscosity coefficients, temperature-associated density changes, and changes in radial loads and rotational speeds could significantly impact the fatigue life of ACBBs. The proposed fatigue life formula is expected to increase the accuracy of ACBB fatigue life predictions.
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