To develop a technology to diagnose the fault of dampers applied to railway vehicles and to set criteria, test runs were performed to measure damping force and displacement acting on a lateral damper during vehicle operation. Normal damper and fault damper were installed on a test train. Damper force and velocity of the lateral damper during test running were measured. Distributions of damper force and velocity representing the state of the damper had the same distribution in repeated tests. Distribution of the damper force and velocity was consistently uniform regardless of the train driving direction. Thus, the effect of train driving direction on damper force and velocity distribution was insignificant. The fault of the damper appeared to have a direct effect on the distribution of the damper force, suggesting that the fault of the damper could be sufficiently diagnosed just by monitoring the force of the damper. Especially, when comparing the velocity-force distribution, the fault damper showed a clear difference from a normal damper. Results of this paper could be used for developing a technology for diagnosing damper fault for railway vehicles in the future.

The effectiveness of applying tap water method to reduce the generation of nano-sized wear particles from wheel-rail contacts in the aspect of air quality was investigated. A twin-disk rig was utilized to simulate the generation of airborne wear particles resulting from wheel-rail contacts. Slip rates ranging from 0 to 3% were continuously generated to simulate various railway vehicle dynamics. Dry and tap water application conditions (7 L/min) were tested. The mass concentration of wear particles with sizes below 560 nm generated during tests was measured using a Fast Mobility Particle Sizer (FMPS). Particles measured in the slip zone (0 to 3%) were categorized into PM0.02, PM0.03, PM0.1, and PM0.56 for analysis. Results indicated a significant decrease in mass concentration of particles with sizes above 30 nm, while those with sizes below 30 nm showed an increase. Particle reduction rate was -217.2% for PM0.02, -58.5% for PM0.03, 84.5% for PM0.1, and 90.3% for PM0.56. It should be noted that a negative reduction rate indicates an increase in the amount of particle generation. This study demonstrates that the application of tap water is effective in improving air quality by reducing the generation of nano-sized wear particles overall.

The surface of railway wheels running on rails is subject to damage due to rail and frictional wear, damage from wheel tread and flange wear caused by curved track operations, and damage from flats and concave wear due to braking friction heat from brake shoes. Although the surface of wheels is regularly reprofiled through periodic grinding cycles, damage occurring to the wheel surface during operation can lead to deteriorated ride quality and potential failure due to crack propagation. In domestic railway components technical standards, wheel integrity is mandated to be demonstrated through non-destructive testing. To prevent and detect failures caused by damage occurring on railway wheels, it is necessary to develop methods that could detect and evaluate surface damage. The present study investigated a method for detecting and evaluating surface damage on railway wheels using electromagnetic imaging. Results demonstrated that defects with a length of 10 mm, a width of 0.8 to 1.0 mm, and a depth of 0.2 to 1.0 mm could be adequately detected using electromagnetic scan images.

In mechanical braking systems, there are hot spots on the surface of a braking disc due to thermal deformation with a high thermal gradient. Controlling such hot spots is important for extending the life of a braking disc. In this study, surface temperatures of railway brake discs were monitored using infrared (IR) thermal imaging technique. A highspeed infrared camera with a maximum speed of 380 Hz was used to monitor surface temperature changes of the braking disc. Braking tests were performed with a full-scale dynamometer. During the braking test, the surface temperature change of the braking disc were monitored using a high-speed infrared camera. Hot spots and thermal damage observed on the surface of railway brake discs during braking tests were quantitatively analyzed using infrared thermographic images. Results revealed that monitoring disc surface temperature using IR thermographic technique can be a new method for predicting surface temperature changes without installing a thermocouple inside the disc.

Railway axles are among critical components ensuring safe and efficient train operations. They are particularly susceptible to damage mechanisms such as fretting wear and fatigue. Fretting induced by high contact pressure and microslip between contact surface can significantly deteriorate fatigue strength at the contact edge of the press-fit section. Recent research has been conducted to enhance axle strength and reliability. However, fretting wear or microcrack formation at the wheel-press-fit zone of axles is still an active area of investigation. Accurately analyzing fretting wear is challenging due to its sensitivity to numerous factors such as changes in friction coefficient, influence of wear particles, and selection of an appropriate wear model. This paper aimed to establish a comprehensive analysis method for fretting wear in interference-fitted axles using finite element analysis (FEA) and numerical analysis techniques. Two wear models were applied in simulations: an Archard wear model and an energy-based wear model. Analysis results were compared with experimental data from rotating bending fatigue press-fit specimens. This comparison will help validate the proposed analysis method and assess the effectiveness and accuracy of different wear models in predicting fretting wear in press-fit axles.

This study presents a method for inspecting ship block wall painting using a cooperative robot. The robot used in this study is a representative example of a human-collaborative robot system. The end-effector of the robot is equipped with a depth camera, designed in an eye-in style. The camera is used to measure and evaluate the thickness of the paint applied to the iron plate, simulating the conditions of ship block wall painting. To improve the accuracy of the recognition, an object detection algorithm with rapid computation and high accuracy was utilized. The algorithm was used to identify and outline the paint areas using the Canny edge algorithm. The proposed method successfully demonstrated the precision of paint area recognition by clearly identifying the center point and outline of the areas. Comparing the paint thickness measurements with laser distance measurements confirmed the effectiveness of the proposed method.

With the increasing severity of global warming, there is a growing need for eco-friendly vehicles to reduce greenhouse gas emissions. However, the expansion of charging infrastructure is struggling to keep up with the rising number of electric vehicles due to space constraints and installation costs. This paper aims to address this issue by proposing an autonomous driving algorithm for a mobile robot-based movable charging system for electric vehicles, as an alternative to traditional stationary charging stations. Our paper introduces a rule-based path planning algorithm for autonomous robot-based charging systems. To achieve this, we employ the A^* (A-star) algorithm for global path planning towards the charging request position, while utilizing the Dynamic Window Approach (DWA) algorithm for generating avoidance paths around obstacles in the parking lot. The avoidance path generation algorithm differentiates between dynamic and static obstacles, with specific algorithms formulated for each type of obstacle. Finally, we implement the suggested algorithm and verify its performance through simulation.

The Forming Limit Diagram (FLD) is a criterion used to assess the formability of sheet metal during a manufacturing process. Traditionally, FLDs are obtained through manual measurements using Mylar tape or through the use of automatic deformation measurement systems such as ARMIS and ARGUS. However, the use of Mylar tape is not user-friendly and can result in errors. Additionally, the cost of using automatic measuring equipment is high. To address these challenges, we propose a method that utilizes a low-cost USB digital microscope and the Python-based open-source library, OpenCV, to obtain forming limit diagrams. This approach allows for the measurement of deformation on specimens by analyzing circles printed on them. To evaluate the performance of this method, a circular grid was printed on a sus430 0.3 t specimen and a nakajima test was conducted. The strain data obtained using this system was then compared to the FLD obtained with the ARGUS system. The results confirmed that the formability of sheet metal can be assessed at a lower cost using our proposed method.

As system performance continues to improve at higher resolutions, it becomes increasingly important to establish standards for imaging degradation caused by optical windows. In this study, random surface shapes were simulated on large area optical windows with peak-to-valley (P-v) values of 0.25, 0.5, and 1.0 λ. Modulation Transfer Function (MTF) values were derived for 1,000 cases per P-v value using Monte-Carlo simulations. The specifications achieved a surface accuracy of 0.5 λ and a parallelism of 0.01 mm. MTF measurements showed that the system MTF was 13.5% prior to the installation of the optical window, and 13.1% after installation. This indicates a degradation rate of approximately 3%.