Development and research on electric vehicles in power transmission system are increasing as the demand for ecofriendly and autonomous vehicles increases across the industry. In order to reduce noise, research on high efficiency and low noise due to electrification of the gearbox system is being actively conducted, such as applying design technology to optimize the shape of the gear and increase rigidity. In particular, research on low noise is active because the noise of the electric gearbox could be easily recognized in a vehicle, even with small noise due to its frequency characteristics. Therefore, in this study, effects of main specifications of gears on noise and power loss were studied and analyzed through a Parametric Study. Characteristics of the proportional relationship between noise and power loss according to major specifications were analyzed. Based on study results, NVH analysis in the gear system was performed. After that, actual data were secured through test measurements and a noise reduction effect of 4.4 dB was confirmed.

A pod mounted on an aircraft external must be installed on an aircraft after its structural safety is verified under flight conditions. This paper presents methods of flight load and test load generation. Evaluation of test result data and standards for failure mode are also presented. First of all, to verify the static structural stability, flight loads for the aircraft maneuvering conditions were calculated. Finite element analysis was then performed with flight loads. As a result of the analysis, structures were verified to have a margin of safety for a given design requirement. In addition, it was confirmed that the launcher tube had enough rigidity to support the missile. Thus, the role of stinger such as longeron and hardback was insignificant. Finally, based on results of tests and analysis, the static structural stability of pod was substantiated and the reliability and effectiveness of the analysis model were obtained. These results and dynamic stability verification results suggest that an optimal design is necessary.

This study introduces a novel tip-tilt-piston aligner based on aligned folded beam flexure. It was designed to enhance precision positioning by minimizing parasitic motion. Through finite element analysis, we compared this aligner with a traditional folded beam flexure-based mechanism, revealing a remarkable 135% increase in translational stiffness and superior rotational stiffness ratios. These advancements are expected to reduce parasitic motion arising from actuator misalignment and external disturbances, ultimately elevating positioning accuracy. The aligner’s suitability as a guiding device was affirmed and optimal actuator placement positions were determined. This research provides valuable insights into precision positioning mechanism design, underscoring the role of flexure geometry and precise actuator placement in minimizing parasitic motion for improved accuracy.

A magnetic levitation system (MLS) controls the position of a steel ball with the magnetic force of the electromagnetic actuator. A disturbance observer (DOB) could improve the disturbance rejection and command tracking performance of the voltage-controlled MLS. This paper studied control boost of MLS using current and position DOB. The current-controlled MLS had a higher control performance than the voltage-controlled MLS. The combination of PID position and PI current controls provided stable levitation and a wide operation range of MLS. When DOB was applied to PI current control, it could compensate for inductance change according to the position of the steel ball. In addition, when another DOB was introduced to the PID position control, it improved the disturbance removal performance. Finally, we discussed the effectiveness and limitations of the DOB-based current and position control by measuring closed-loop frequency responses.

This study developed a defect-detecting system for automotive wheel nuts. We proposed an image processing method using OpenCV for efficient defect-detection of automotive wheel nuts. Image processing method focused on noise removal, ratio adjustment, binarization, polar coordinate system formation, and orthogonal coordinate system conversion. Through data collection, preprocessing, object detection model training, and testing, we established a system capable of accurately classifying defects and tracking their positions. There are four defect types. Types 1 and 2 defects are defects of products where the product is completely broken circumferentially. Types 3 and 4 defects are defects are small circumferential dents and scratches in the product. We utilized Faster R-CNN and YOLOv8 models to detect defect types. By employing effective preprocessing and post-processing steps, we enhanced the accuracy. In the case of Fast RCNN, AP values were 0.92, 0.93, 0.76, and 0.49 for types 1, 2, 3, and 4 defects, respectively. The mAP was 0.77. In the case of YOLOv8, AP values were 0.78, 0.96, 0.8, and 0.51 for types for types 1, 2, 3, and 4 defects, respectively. The mAP was 0.76. These results could contribute to defect detection and quality improvement in the automotive manufacturing sector.

The demand for flexible electronic materials used in wearable devices has experienced a significant surge in recent years. Wearable devices typically incorporate an electronic material or system that can be mounted on a human body. It is imperative that these materials are composed of substances compatible with the human body. Consequently, numerous studies have been undertaken to develop flexible electronic devices with various performance capabilities. In this study, nanowire patterns were manufactured on nanofibers and utilized as patches. To create a nanowire pattern, a direct-write spraying process was employed to investigate changes in electrical characteristics using process variables. The process involved depositing silver nanowires on the surface of nanofibers using a pneumatic spray nozzle. Generated patterns were found to be suitable for use as sensors capable of withstanding skin-attached deformation.

In this study, we proposed an AI-algorithm for face mask recognition based on the MobileNetV2 network to implement automatic door control in intensive care units. The proposed network was constructed using four bottleneck blocks, incorporating depth-wise separable convolution with channel expansion/projection to minimize computational costs. The performance of the proposed network was compared with other networks trained with an identical dataset. Our network demonstrated higher accuracy than other networks. It also had less trainable total parameters. Additionally, we employed the CVzone-based machine learning model to automatically detect face location. The neural network for mask recognition and the face detection model were integrated into a system for real-time door control using Arduino. Consequently, the proposed algorithm could automatically verify the wearing of masks upon entry to intensive care units, thereby preventing respiratory disease infections among patients and medical staff. The low computational cost and high accuracy of the proposed algorithm also provide excellent performance for real-time mask recognition in actual environments.

With the increasing use of portable devices, the safety and efficiency of wireless chargers have become significant concerns. Wireless chargers can cause battery damage, deformation, and failure of the charging module due to the high temperatures generated during the charging process. Thus, the importance of thermal management has been increasingly emphasized. In this study, we experimentally confirmed that cooling performance was improved by applying phase change material (PCM) to the heat-generating parts of the wireless charger. The cooling performance of the PCM was analyzed using Ansys Fluent, the component temperature was measured with an infrared camera, and 3D thermal deformation was measured with a DIC measurement device. Electromagnetic field, thermal, fluid, and structural coupled analyses were performed to investigate the impact of thermal deformation caused by wireless charging. The results showed that the temperature and deformation error was within 3% of the coupled analysis results, and the proposed electromagneticthermal-fluid-structural coupled analysis enabled more accurate simulation prediction of the physical coupling process inside the wireless charger.

Rails are important facilities related to safe running of trains. When buckling occurs due to thermal expansion, serious safety accidents such as train derailment can occur. Currently, operating organizations are building expensive temperature monitoring systems and automatic watering devices. However, they have limitations for universalization due to their costs. Recently, long-term rail temperature reduction effect has been demonstrated by applying thermal insulation paint to rail surface. However, when coating the rail surface with paint, it increases the difficulty of detecting defects through nondestructive testing, which is one of the important elements of rail maintenance. To solve this problem, previous studies have proposed a detachable thermal insulation fabric by coating the surface of a fabric with thermal insulation paint and attaching a magnetic material. In this study, effect of thermal insulation performance according to manufacturing method was analyzed to derive the optimal performance of the previously developed thermal insulation fabric. Experiment results confirmed that paint weight increased when the roller method was used compared to the spray method with temperature reduction performance improved. Finally, the most efficient and optimal paint weight ratio was derived when the roller method was applied.

A feasibility study of electrically assisted solid-state spot joining (EASSJ) of dissimilar aluminum alloys for automobile structures was conducted. EASSJ of dissimilar automotive aluminum alloys (AA6451 and AA6014) was conducted by simultaneously applying step-by-step current and compressive load to the faying interface (lap spot joining), while the temperature was controlled to be lower than melting points of joining alloys. To evaluate the soundness of the joint, a nugget pull-out fracture mode under shear tensile test was set as a criterion. Microstructure analysis was also conducted to evaluate characteristics of the joint. Experimental results suggest that the EASSJ is clearly feasible in joining dissimilar aluminum alloys for automobile structures.