• Title/Summary/Keyword: Railway Accidents

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Analytical Behavior of Concrete Derailment Containment Provision(DCP) according to Train Impact Loading (열차 충돌하중에 대한 콘크리트 일탈방호시설물(DCP)의 해석적 거동 검토)

  • Yi, Na-Hyun;Kim, Ji-Hwan;Kang, Yun-Suk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.604-613
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    • 2018
  • In recent years, numerous train derailment accidents caused by deterioration and high speed technology of railways have increased. Guardrails or barriers of railway bridges are installed to restrain and prevent the derailment of the train body level. On the other hand, it can result in a high casualties and secondary damage. Therefore, a Derailment Containment Provision (DCP) within the track at the wheel/bogie level was developed. DCP is designed for rapid installation because it reduces the impact load on the barrier and inertia force on the steep curve to minimize turnover, fall, and trespass on the other side track of the bridge. In this paper, DCP was analyzed using LS-Dyna with a parameter study as the impact loading location and interface contact condition. The contact conditions were analyzed using the Tiebreak contact simulating breakage of material properties and Perfect bond contact assuming fully attached. As a result, the Tiebreak contact behaved similarly with the actual behavior. In addition, the maximum displacement and flexural failure was generated on the interface and DCP center, respectively. The impact analysis was carried out in advance to confirm the DCP design due to the difficulties of performing the actual impact test, and it could change the DCP anchor design as the analysis results.

A Study on the Wireless Communication Method for Emergency Broadcasting System in Metro Environments (도시철도용 비상방송시스템을 위한 무선통신방식 연구)

  • Jang, Soo-Hyun;Shin, Dae-Kyo;Yoon, Sang-Hun;Jung, Han-Gyun;Jin, Seong-Keun;Lim, Ki-Taeg
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.6
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    • pp.202-210
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    • 2018
  • Recently, the subway running in metro environments has a problem in securing the safety of passengers due to the failure of announcement in emergency situations such as breakdown, train accidents and power outage in the underground tunnels. Thus, there is a need to develop an emergency broadcasting system that can provide the announcement to all passenger cars in any emergency situations on the railway route. In this paper, the applicability of various wireless communication technologies for the emergency broadcasting system through the measurement campaign was examined in Seoul metropolitan subway. A WAVE(Wireless Access in Vehicular Environments) is communication technology that can use 5.9GHz dedicated frequency band without charge and it is possible to directly communicate between terminals over 200m without the help of additional relay. Especially, it confirms robust communication performance in the various metro environments, and therefore, it is considered to be suitable as a communication method of a radio-connected emergency broadcasting system for urban subway.

Development of penetration rate prediction model using shield TBM excavation data (쉴드 TBM 현장 굴진데이터를 이용한 굴착속도 예측모델 개발)

  • La, You-Sung;Kim, Myung-In;Kim, Bumjoo
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.21 no.4
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    • pp.519-534
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    • 2019
  • Mechanized tunneling methods, including shield TBM, have been increasingly used for tunnel construction because of their relatively low vibration and noise levels as well as low risk of rock-falling accidents. In the excavation using the shield TBM, it is important to design penetration rate appropriately. In present study, both subsurface investigation data and shield TBM excavation data, produced for and during ${\bigcirc}{\bigcirc}{\sim}{\bigcirc}{\bigcirc}$ high-speed railway construction, were analyzed and used to compare with shield TBM penetration rates calculated using existing penetrating rate prediction models proposed by several foreign researchers. The correlation between thrust force per disk cutter and uniaxial compressive strength was also examined and, based on the correlation analysis, a simple prediction model for penetration rate was derived. The prediction results using the existing prediction models showed approximately error rates of 50~500%, whereas the results from the simple model proposed from this study showed an error rate of 15% in average. It may be said, therefore, that the proposed model has higher applicability for shield TBM construction in similar ground conditions.

Detection Fastener Defect using Semi Supervised Learning and Transfer Learning (준지도 학습과 전이 학습을 이용한 선로 체결 장치 결함 검출)

  • Sangmin Lee;Seokmin Han
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.91-98
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    • 2023
  • Recently, according to development of artificial intelligence, a wide range of industry being automatic and optimized. Also we can find out some research of using supervised learning for deteceting defect of railway in domestic rail industry. However, there are structures other than rails on the track, and the fastener is a device that binds the rail to other structures, and periodic inspections are required to prevent safety accidents. In this paper, we present a method of reducing cost for labeling using semi-supervised and transfer model trained on rail fastener data. We use Resnet50 as the backbone network pretrained on ImageNet. At first we randomly take training data from unlabeled data and then labeled that data to train model. After predict unlabeled data by trained model, we adopted a method of adding the data with the highest probability for each class to the training data by a predetermined size. Futhermore, we also conducted some experiments to investigate the influence of the number of initially labeled data. As a result of the experiment, model reaches 92% accuracy which has a performance difference of around 5% compared to supervised learning. This is expected to improve the performance of the classifier by using relatively few labels without additional labeling processes through the proposed method.

Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks (Deep Convolution Neural Networks 이용하여 결함 검출을 위한 결함이 있는 철도선로표면 디지털영상 재 생성)

  • Kim, Hyeonho;Han, Seokmin
    • Journal of Internet Computing and Services
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    • v.21 no.6
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    • pp.23-31
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    • 2020
  • This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

A Study on Legal and Institutional Improvement Measures for the Effective Implementation of SMS -Focusing on Aircraft Accident Investigation-

  • Yoo, Kyung-In
    • The Korean Journal of Air & Space Law and Policy
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    • v.32 no.2
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    • pp.101-127
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    • 2017
  • Even with the most advanced aviation technology benefits, aircraft accidents are constantly occurring while air passenger transportation volume is expected to double in the next 15 years. Since it is not possible to secure aviation safety only by the post aircraft accident safety action of accident investigations, it has been recognized and consensus has been formed that proactive and predictive prevention measures are necessary. In this sense, the aviation safety management system (SMS) was introduced in 2008 and has been carried out in earnest since 2011. SMS is a proactive and predictive aircraft accident preventive measure, which is a mechanism to eliminate the fundamental risk factors by approaching organizational factors beyond technological factors and human factors related to aviation safety. The methodology is to collect hazards in all the sites required for aircraft operations, to build a database, to analyze the risks, and through managing risks, to keep the risks acceptable or below. Therefore, the improper implementation of SMS indicates that the aircraft accident prevention is insufficient and it is to be directly connected with the aircraft accident. Reports of duty performance related hazards including their own errors are essential and most important in SMS. Under the policy of just culture for voluntary reporting, the guarantee of information providers' anonymity, non-punishment and non-blame should be basically secured, but to this end, under-reporting is stagnant due to lack of trust in their own organizations. It is necessary for the accountable executive(CEO) and senior management to take a leading role to foster the safety culture initiating from just culture with the safety consciousness, balancing between safety and profit for the organization. Though a Ministry of Land, Infrastructure and Transport's order, "Guidance on SMS Implementation" states the training required for the accountable executive(CEO) and senior management, it is not legally binding. Thus it is suggested that the SMS training completion certificates of accountable executive(CEO) and senior management be included in SMS approval application form that is legally required by "Korea Aviation Safety Program" in addition to other required documents such as a copy of SMS manual. Also, SMS related items are missing in the aircraft accident investigation, so that organizational factors in association with safety culture and risk management are not being investigated. This hinders from preventing future accidents, as the root cause cannot be identified. The Aircraft Accident Investigation Manuals issued by ICAO contain the SMS investigation wheres it is not included in the final report form of Annex 13 to the Convention on International Civil Aviation. In addition, the US National Transportation Safety Board(NTSB) that has been a substantial example of the aircraft accident investigation for the other accident investigation agencies worldwide does not appear to expand the scope of investigation activities further to SMS. For these reasons, it is believed that investigation agencies conducting their investigations under Annex 13 do not include SMS in the investigation items, and the aircraft accident investigators are hardly exposed to SMS investigation methods or techniques. In this respect, it is necessary to include the SMS investigation in the organization and management information of the final report format of Annex 13. In Korea as well, in the same manner, SMS item should be added to the final report format of the Operating Regulation of the Aircraft and Railway Accident Investigation Board. If such legal and institutional improvement methods are complemented, SMS will serve the purpose of aircraft accident prevention effectively and contribute to the improvement of aviation safety in the future.

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