• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.758-764
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• 2019

The chassis of the Korean light tactical vehicle adopts a frame-on-body structure that uses lightweight design technology in terms of equipment operating characteristics. Military vehicles are operated in much harsher conditions compared to civilian vehicles, including mountainous terrain, especially steep slopes. Due to this characteristic, frame-welded cracks were found on some military vehicles. Therefore, in this paper, road damage analysis was conducted by identifying various roads including the military unit's road. The result confirmed that the operating environment of some military units' tactical road was much harsher than the endurance road test condition. A solution was derived through defect analysis, design review, and actual vehicle driving test. This study can be used as a reference by suggesting the development direction for the durability test of a new vehicle.

• Fire Science and Engineering
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• v.26 no.4
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• pp.70-76
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• 2012

This paper deal with vehicle fire caused by damage of diesel particulate filter (DPF) on diesel passenger vehicles. In order to reduce particulate matters included exhaust gases, a DPF in the exhaust system were installed diesel vehicles. A DPF was broken by excessively trapped particulate matters, regeneration error with a malfunction of ECU and defect of suction system such as swirl valve. If the DPF was broken, hot exhaust gases was released to the bottom of vehicle and released hot exhaust gases lead to occur the fire through combustible materials around the exhaust system. When a fire happened in the diesel vehicle caused by damage of DPF, silicate inorganic compounds were attached to the exhaust ventilation pipe and muffler. The silicate inorganic compounds were created by DPF combustion consisting of raw material ceramics. If the silicate inorganic compounds attached to the tail pipe in the diesel passenger vehicles, its fire cause will be assumed damage of DPF.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.375-380
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• 2018

This paper proposes a classification method using the Convolutional Neural Network(CNN) which can obtain the type of trucks from the input image without the feature extraction step. To automatically classify vehicle images according to the type of truck cargo box, the top view images of the vehicle are used as input image and we design the structure of the CNN suitable for the input images. Learning images and correct output results is generated and the weights of neural network are obtained through the learning process. The actual image is input to the CNN and the output of the CNN is calculated. The classification performance is evaluated through comparison CNN output with actual vehicle types. Experimental results show that vehicle images could be classified with more than 90 percent accuracy according to the type of cargo box and this method can be used for pre-classification for inspecting loading defect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.72-81
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• 2023

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.5
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• pp.423-428
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• 2010

In this paper, we analyzed the characteristics of thermal deformation of the TPS which is a core part of engine in vehicle by measuring out-of-plane deformation using ESP!. Inspection area of a test piece was minimized to 5 cm by 5 cm by using a high resolution CCD and a zoom lens. 4-step phase shifting method was used along with phase unwrapping algorithm to get a continuous phase map, configurations and deformations were displayed as 3D images. When heating the test pieces while maintaining the temperature at about $70^{\circ}C$, the out-of-plane deformations were measured. The results showed that a test piece with longer distance traveled tends to show larger thermal deformation, we could observes a convex shaped deformation on the surface. The inner defect sample, we could monitor discontinuous pattern phase map, and a concave shaped deformation on the surface.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.112-119
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• 2021

Purpose: This study is based on the detailed inspection data for the last 6 years of fire-fighting high ladder vehicles, fire-fighting inflected ladder vehicles, fire-fighting chemical vehicles and fire-fighting pump vehicles used in front-line fire departments. The purpose is to contribute to the technological development of fire-fighting vehicles by grasping the implementation status of each city and province, the rate of defects, and the occurrence of defects by year. Method: The implementation status by city and province, defect incidence rate, and defect occurrences by year were analyzed. Result: From 2012 to 2017, when the average of 230 or more overhaul vehicles was requested, the results of each city/province show slight fluctuations, but the number of defects gradually decreased due to the old fire-fighting vehicle replacement project and the response of fire vehicle manufacturers. Conclusion: In the case of fire-fighting ladders, the incidence rate of defects was found to be in the order of elevator device, electric device, ladder device, and pneumatic supply device. And in the case of the fire fighting ladder, it was confirmed that the incidence of defects appeared in the order of the refractive ladder, hydraulic cylinder, hydraulic oil, and pneumatic supply device. In the case of fire-fighting chemical vehicles, it was confirmed that defects occurred in the powder fire extinguishing device, fire pump, vacuum pump, and pneumatic supply device.

• Journal of Ocean Engineering and Technology
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• v.24 no.4
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• pp.38-46
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• 2010

The wall thinning phenomenon of pipes was simulated as metal loss due to erosion and corrosion. Such wall thinning defects in the pipes of power plants are a very important safety consideration. In this study, we analyzed wall thinning defects that occurred by weld bead of weld zone of boost pump recirculation pipe. From the results of the analysis of pipe failures, numerical analysis was performed by Fluent v6.3.26 using the standard k-$\varepsilon$ model of the weld bead shape, such as an elliptical or a spherical shape, on the inner wall of the pipe. Using the results obtained, we showed the overlap effect by cavitations corrosion and erosion-corrosion at the bottom of the wall-thinning defect.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.87-94
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• 2005

This paper describes the method of detecting the region of vehicle number plate in colored car image with number plate. Vehicle number plate region generally shows formula colors in accordance with type of car. According to this, we use the method to combine a color ingredient H of HSI color model and a color ingredient Q of YIQ color model. However, the defect which a total operation time takes much exists if it uses such method. Therefore, in this paper, the concurrent accomplishes a candidate area extraction operation as draw a color H and Q ingredient among steps of extracting a region of vehicle number Plate. After the above step, as a next step in combination with color H and Q we can accomplish an region extraction fast by comparing to candidate regions extracted from each steps not to do a comparison operation to all of image pixel information. We also show implementation results Processed at each steps and compare with extraction time according to image resolutions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.135-143
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• 2000

The vision system is easy to use the exclusive use as a independent computer system but it is not much popularization by reason of expensive and difficult to adapt to the various fields, because it is easy to the existed computer system, the price is cheap and also it can use to the various measurement purpose which user wanted and programed. The measurement method of the vehicle axle casing nut welding part is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual length of the standard specimen and the length of image, to measure the ratio between the actual product and the camera image. A defect is found by the assembled visual inspection system. The inspection algorithm which estimates the quality of welded product is developed and also, the software program which processes the automatic test function of the inspection system. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• Journal of Korea Foundry Society
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• v.29 no.5
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• pp.238-243
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• 2009

This study has been carried out to investigate the cooling ability improvement of diecasting mold by decompression cooling system. The decompression cooling system was applied to the new/used oil pump cover molds. The temperature of the surface mold applied the decompression cooling system fell to 15 degrees, especially in case of the used mold. The defect ratio of the oil pump cover manufactured by decompression cooling system has decreased from 2.8 percent to 0.2 percent. According to the results of the cooling ability improvement of diecasting mold by decompression cooling system, the decompression degree and supply pressure were set up the control item to apply the decompression cooling system to the diecasting mold in the industry field.