• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.81-88
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• 2015

Infrastructure such as tracks, catenary, rolling stock and signaling systems, and close interface with the human factors of train drivers, shunting staff and maintenance staff are required for train operations. Safety management is the most essential part for the functioning of a train. In line with the safety management, each rail operator has a safety guidance system and the Ministry of Land, Infrastructure and Transport operates Railway Safety Inspector system. Safety Inspector System is to train employees working in the field to be aware of rules and regulations, and to improve identified risk factors. Hence, it is necessary to establish systematic training and inspection methods for safety guidance staff and make clear the roles and responsibilities of safety inspectors according to the Occupational Safety and Health Act, and safety instructors for several inspections according to the Railroad Safety Act.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.6-7
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• 2017

• Journal of the Korean Society for Railway
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• v.12 no.3
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• pp.364-369
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• 2009

Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection doe to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

• Journal of the Korean Society for Railway
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• v.18 no.1
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• pp.1-7
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• 2015

Maintenance and repair devices used for the inspection of the main parts of domestic railway vehicles have been imported from abroad. Especially, one of the representative domestic devices, the 'Wheel Profile Inspector System (WPIS)', was made by benchmarking foreign devices; this vehicle has been operated in the field. However, problems such as the reliability and performance of the WPIS in operation have appeared. In this study, in order to improve the precision and reliability of the WPIS for maintenance and inspection of railway vehicle wheels, the researchers improved the railway vehicle's WPIS by applying high-speed vision camera technology and an optimized image algorithm. The test results show that the reliability of the developed WPIS improved by approximately 10.4% compared to that of the conventional system.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.389-394
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• 2019

In case of damaged timber sleepers, maintenance is carried out according to the track inspection standard. However, it is difficult to detect the extent of damage on the bridge, and maintenance is depended on inspector's judgment. In this study, we propose to improve the evaluation criterion of timber sleepers for the ballast-less tracks on serviced urban railway bridge. The timber sleepers on railway bridge was classified according to degree of damage, and damage scores were calculated for each damage grade. Also we have improved the maintenance system of the timber sleepers through the history management system of the individual timber sleepers on railway bridge. As a results, it was judged that systematic management of timber sleepers could be possible during maintenance.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.872-898
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• 2007

Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection due to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.188-193
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• 2008

According to introduce KTX in Korea, rail-road bridge section of KTX was increased approximately 50% of the total length. Bridge is required periodic inspection and check to prevent accident and hazard because various damage which have effects on traffic and replacement of damaged parts is difficult. Specifically, the train as large-scale transportation because accidents led to great damage, preventing these accidents are critical. Well-organized management and maintenance systems are required to prevent the accidents. In the case of roadway bridge, bridge inspection vehicle is used to deploy inspectors in roadway bridge. However, this method requires a lot of time and efforts, and inspectors are exposed to potential hazard. Also, surrounding environment like poor lighting system or electric wire could harm the inspector while repairing. Due to this reason, automatic repairing and inspecting system have been introduced to replace the old methods. Management system of the railroad bridge track for trains uses various advanced equipments, but whereas roadway bridge management system is lacking these efforts. As a result of that, this study looks over the existing management method. and review the method to apply the Bridge Inspection Robot in railroad bridge. Moreover, this study suggests future management technology using inspection robot.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.505-510
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• 2024

Since rolling contact fatigue cracks can always occur on the rail surface, which is the contact surface between wheels and rails, railway rails require thorough inspection and diagnosis to thoroughly inspect the condition of the cracks and prevent breakage. Recent detailed guidelines on the performance evaluation of track facilities present the requirements for methods and procedures for track performance evaluation. However, diagnosing and grading rail surface damage mainly relies on external inspection (visual inspection), which inevitably relies on qualitative evaluation based on the subjective judgment of the inspector. Therefore, in this study, we conducted a deep learning model study for rail surface defect detection using Fast R-CNN. After building a dataset of rail surface defect images, the model was tested. The performance evaluation results of the deep learning model showed that mAP was 94.9%. Because Fast R-CNN has a high crack detection effect, it is believed that using this model can efficiently identify rail surface defects.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.585-590
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• 2024

In this study, rail surface defects are increasing due to the aging of urban railway rails, but in the detailed guidelines for track performance evaluation established by the country, rail surface damage is inspected with the naked eye of engineers and simple measuring tools. With the recent enactment of the Track Diagnosis Act, a large budget has been invested and the volume of rail diagnosis is rapidly increasing, but it is difficult to secure the reliability of diagnosis results using labor-intensive visual inspection techniques. It is very important to discover defects in the rail surface through periodic track tours and visual inspection. However, evaluating the severity of defects on the rail surface based on the subjective judgment of the inspector has significant limitations in predicting damage inside the rail. In this study, the rail internal crack characteristics due to rail surface damage were studied. In field measurements, rail surface damage locations were selected, samples of various damage types were collected, and the rail surface damage status was evaluated. In indoor testing, we intend to analyze the correlation between rail surface defects and internal defects using a electron scanning microscope (SEM). To determine the crack growth rate of urban railway rails currently in use, the Gaussian probability density function was applied and analyzed.