• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.102-109
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• 2019

This paper describes the design of the circuit card assembly to eliminate the communication error on a servo control unit installed in the automated resupply vehicle K56. K56 is a weapon system that automates the supply and loading of ammunition on the K-55A1 self-propelled artillery. As the core item responsible for ammunition movement control, the servo control unit is required to have good communication stability and reliability, but the conventional unit has recognized a problem that communication error intermittently occurs, resulting in an emergency stop phenomenon. We analyzed the communication signal of the servo control unit and identified the failure cause of the circuit card assembly to solve this problem. In addition, the signal interference in data/address line of the circuit card assembly was confirmed through analysis of the failure cause, and redesigned to avoid the interference, such as adjustment of the distance between communication lines and position change. Finally, the proposed cause analysis and redesign were verified through the component of servo control unit and attachment test on K56. We expected these study results to be used as reference for the design of other similar items.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• International Journal of Automotive Technology
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• v.4 no.2
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• pp.77-86
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• 2003

How to compare the environmental damage caused by vehicles with different foe]s and drive trains\ulcorner This paper describes a methodology to assess the environmental impact of vehicles, using different approaches, and evaluating their benefits and limitations. Rating systems are analysed as tools to compare the environmental impact of vehicles, allowing decision makers to dedicate their financial and non-financial policies and support measures in function of the ecological damage. The paper is based on the "Clean Vehicles" research project, commissioned by the Brussels Capital Region via the BIM-IBGE (Brussels Institute for the Conservation of the Environment) (Van Mierlo et at., 2001). The VriJe Universiteit Brussel (ETEC) and the universite Libre do Bruxelles (CEESE) have jointly carried out the workprogramme. The most important results of this project are illustrated in this paper. First an overview of environmental, economical and technical characteristics of the different alternative fuels and drive trains is given. Afterward the basic principles to identify the environmental impact of cars are described. An outline of the considered emissions and their environmental impact leads to the definition of the calculation method, named Ecoscore. A rather simple and pragmatic approach would be stating that all alternative fuelled vehicles (LPG, CNG, EV, HEV, etc.) can be considered as ′clean′. Another basic approach is considering as ′clean′ all vehicles satisfying a stringent omission regulation like EURO IV or EEV. Such approaches however don′t tell anything about the real environmental damage of the vehicles. In the paper we describe "how should the environmental impact of vehicles be defined\ulcorner", including parameters affecting the emissions of vehicles and their influence on human beings and on the environment and "how could it be defined \ulcorner", taking into account the availability of accurate and reliable data. We take into account different damages (acid rain, photochemical air pollution, global warming. noise, etc.) and their impacts on several receptors like human beings (e.g., cancer, respiratory diseases, etc), ecosystems, or buildings. The presented methodology is based on a kind of Life Cycle Assessment (LCA) in which the contribution of all emissions to a certain damage are considered (e.g. using Exposure-Response damage function). The emissions will include oil extraction, transportation refinery, electricity production, distribution, (Well-to-Wheel approach), as well as the emission due to the production, use and dismantling of the vehicle (Cradle-to-Grave approach). The different damages will be normalized to be able to make a comparison. Hence a reference value (determined by the reference vehicle chosen) will be defined as a target value (the normalized value will thus measure a kind of Distance to Target). The contribution of the different normalized damages to a single value "Ecoscore" will be based on a panel weighting method. Some examples of the calculation of the Ecoscore for different alternative fuels and drive trains will be calculated as an illustration of the methodology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1655-1665
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• 2014

Dynamic displacements of structures shows general behavior of structures. Generally, It is used to estimate structure condition and trustworthy physical quantity directly. Especially, measuring vertical displacement which is affected by moving load is very important part to find or identify a problem of bridge in advance. However directly measuring vertical displacement of the bridge is difficult because of test conditions and restriction of measuring equipment. In this study, Artificial Neural Network (ANN) is used to suggest estimation method of bridge displacement to overcome constrain conditions, restriction and so on. Horizontal strain and vertical displacement which are measured by appling random moving load on the bridge are applied for learning and verification of ANN. Measured horizontal strain is used to learn ANN to estimate vertical displacement of the bridge. Numerical analysis is used to acquire learning data for axis strain and vertical displacement for applying ANN. Moving load scenario which is made by vehicle type and vehicle distance time using Pearson Type III distribution is applied to analysis modeling to reflect real traffic situation. Estimated vertical displacement in respect of horizontal strain according to learning result using ANN is compared with vertical displacement of experiment and it presents vertical displacement of experiment well.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.629-636
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• 2022

Domestic eco-friendly vehicles currently account for 5.8% of the total registered vehicles in Korea. Hydrogen vehicles, one of the representative eco-friendly vehicles, have grown rapidly as they have been expanded to the market based on the government's policy to boost the hydrogen industry. Therefore, it is time to expand the safety review of hydrogen vehicles in various directions according to the increase in supply. In this study, the effect of internal heat damage was analyzed when a jet flame was generated by a hydrogen car in a road tunnel. It was simulated using Fluent, and the amount of jet flame injection was selected in consideration of the hydrogen tank capacity of commercial hydrogen vehicles for road tunnels. In addition, the study was conducted with the direction of the jet flame and the nozzle distance from the tunnel wall as variables. From the results, when the jet flame erupted in the road tunnel, high radiant heat emission of more than 20 kW/m² was generated in most areas within ±5 m in the longitudinal direction based on the vehicle (spray nozzle) and 5 to 7 m in the lateral direction based on the adjacent tunnel wall.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.745-756
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• 2022

The road tunnel is a semi-closed space that is blocked on all sides except the entrance and exit, and in the event of a fire, the smoke of the fire spreads longitudinally due to heat buoyancy caused by the fire and air currents that always exist in the tunnel. To solve this problem, smoke removal facilities are installed in road tunnels to secure a safe evacuation environment by controlling the direction of movement of smoke or directly smoking at fire points. In urban areas, the service level of urban roads decreases due to the increase in traffic due to the increase in population, and as a solution, the construction of underground roads in urban areas is increasing. When a fire occurs during hydrogen leakage through TPRD of a hydrogen fuel cell vehicle (FCEV), the fire intensity depends on the amount of leakage, and the maximum fire intensity depends on the orifice diameter of the TPRD. Considering the TPRD orifice diameter of 1.8 mm, this study analyzed the diffusion distance of fire smoke according to the wind speed of the roadway and the opening interval of the large exhaust port when the maximum fire intensity was 15 MW. As a result, it was analyzed that air flow in the tunnel could be controlled if the wind speed of the road in the tunnel was less than 1.25 m/s, and smoke could be controlled within 200 m from the fire if the damper interval was 50 m and 100 m.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.59-64
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• 2018

As part of measures to reduce fine dust, the government is promoting a project to convert the fuel of Yard Tractors(YT, tractors operated at ports), from diesel to LNG (Liquefied Natural Gas). While a port having a small number of yard tractors, it is not proper to construct a stationary LNG fueling station and supply LNG to YT due to a problem of BOG (Boil off gas) generation. Therefore, it is necessary to make a regulation and a standard on mobile LNG YT refueling station installation and inspection as an alternative. In this study, we have investigated domestic and foreign mobile LNG refueling cases and refueling standards, including the USA and Europe. In addition, we have suggested the risk reduction method according to the cause after investigation of the cause of LNG accidents. And last, based on the proposed risk reduction measures, we have proposed an amendment to the Regulation of the Urban Gas Business Law in Korea. The proposed mobile LNG YT refueling amendment of the Regulation includes ; maintenance of the safety distance from the protection facility, installation of an interlock device to prevent refueling in places other than the authorized place, installation of the identification system through biometrics, separation of the tank lorry and tow vehicle before refueling, checking the wheel fixed status of tank lorry before refueling, construction of the impounding area, safety measures before, during and after refueling, etc. The safety standards proposed in this study could be used as a reference in establishing standards for mobile LNG vehicle refueling in the near future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.499-506
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• 2019

This paper is concerned with the operating stability of 7kW inverter using SIC hybrid module and verifies the validity of the simulation results by comparing the result of the loss equation and the simulation result, Simulation results using Si module and SiC hybrid module are compared to compare switch loss and diode loss. Through the loss equation calculation, the conduction loss of SiC Hybrid module is 168W, switching loss is 9.3W, diode loss is 10.5nW, When compared with the simulation results, similar values were shown. As a result of comparing the simulation results of the Si module and the SiC Hybrid module, The total device loss of the Si module was 246.2W, and the total device loss of the SiC Hybrid module was 189.9W. The loss difference was 56.3W, which was about 0.8W. thereby verifying the reverse recovery characteristics of the SiC SBD. In addition, temperature saturation test was conducted to confirm the stability of SiC Hybrid module and Si module under high temperature saturation, In the case of the Si module, the output power was stopped at 4kW, and the SiC Hybrid module was confirmed to operate at 7kW. Based on this, an efficiency graph and a temperature graph are presented, and the Si module is graphed up to 4kW and the SiC Hybrid module is graphed up to 7kW.