• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1370-1378
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• 2007

High speed railway bridge is affected on safety of bridge by dynamic amplification effect, when dynamic response of bridge is equal to effect cycle load for rolling stock axle according to high speed operation train. And excessive deformation of structure has negative effect on operation safety of train and comfort of passenger due to fluctuation of wheel load by torsion of track etc. and decrease of contact force on vehicle wheel-rail. To ensure the safety of track and train operation safety, it is have to perform the study on resonance and deformation of structure. That criteria and requirement of railway bridge is limitation of vertical acceleration on deck for dynamic behavior of structure, contact of vehicle wheel and rail, limitation of face distortion and rotation angle of end deck, and limitation of vertical displacement by train. Unlike KYEONGBU High Speed Railway, New constructed HONAM High Speed Railway have to applied the new requirement for dynamic behavior safety according to change of condition which is type of ballast (slab ballast), interval of track, and actual rolling stock load. Therefore, in this paper, it was conformed the dynamic characteristic due to parameter, which related with above mentioned criteria, for steel composite bridges.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.160-166
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• 2010

Railroad level crossing systems are used to prevent train from collisions by informing pedestrians and vehicles of approaching trains on the level crossing. The current detection systems mostly use track-based electrical circuits to detect approaching trains. The making and breaking of the circuit when the train wheel passes along the track sends a signal to barriers that restrict access to the track. Unfortunately, this track-based signal system is vulnerable to malfunctions in certain situations. If the rail becomes rusted due to moisture, weather conditions, or infrequent use, the electrical circuit detection system could fail. Such a failure could lead to a train-vehicle or train-pedestrian collision. This paper suggests a replacement of the electrical circuit-based system with an infrared detection system. The research shows that an infrared detection system improves safety by reducing the frequency of detection failure of the alarming circuit to system.

• Journal of the Korean Society for Railway
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• v.17 no.1
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• pp.28-34
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• 2014

In this paper, a concept design of a rail type ultra-high-speed train is proposed and its dynamic characteristics are analyzed. Instead of the existing solid axle, a new type bogie system and independently rotating wheels are applied in the proposed train. In order to analyze the dynamic characteristics, a multibody dynamic model of a vehicle is developed and the basic validity is verified by eigenvalue analysis. Also, it is shown that the critical speed is improved in comparison to that of existing high-speed train model HEMU-430X. Finally, through 7000R curved track driving analysis at a speed of 550 km/h, the lateral force of the wheels and the derailment quotient are estimated and the applicability of the new concept railway vehicle is confirmed.

• Proceedings of the Korean Reliability Society Conference
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• 2006.05a
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• pp.40-47
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• 2006

Rail car axles are very important parts for safety of passengers and structural integrity of vehicles. The axles are supported by bearings. To seal grease lubricating the bearings of freight cars, a non-contact oil seal has been developed. The developed oil seal is composed of inner plate, outer plate and seal rubber. The friction between axle and housing with the developed oil seal is very low. The seals are designed for a minimum life expectancy of 800,000 kilometers service. In this study, an accelerated durability tests according to AAR Specification M-934-82 were carried out. Developed products satisfy the AAR Specifications.

• 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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.129-137
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• 2007

An algorithm is proposed for estimating axle loads of trucks moving over a bridge by measuring dynamic responses. The bridge was modeled by a beam structure in the current applications of the proposed algorithm. Among the state vectors, measured acceleration was used and displacement was computed from measured strain at the same location. Nodal force vectors were computed by using a ready-made database of equivalent nodal force transformation matrix. The algorithm was examined through simulation studies and laboratory experiments. The effects of measurement noise and velocity error were investigated through simulation studies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.128-139
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• 2017

Railway is one of the public transportation systems along with shipping and aviation. With the recent introduction of high speed train, its proportion is increasing rapidly, which results in the higher risk of catastrophic failures. The wheel bearing to support the train is one of the important components requiring higher reliability and safety in this aspect. Recently, many studies have been made under the name of prognostics and health management (PHM), for the purpose of fault diagnosis and failure prognosis of the bearing under operation. Among them, the most important step is to extract a feature that represents the fault status properly and is useful for accurate remaining life prediction. However, the conventional features have shown some limitations that make them less useful since they fluctuate over time even after the signal de-noising or do not show a distinct pattern of degradation which lack the monotonic trend over the cycles. In this study, a new method for feature extraction is proposed based on the observation of relative frequency energy shifting over the cycles, which is then converted into the feature using the information entropy. In order to demonstrate the method, traditional and new features are generated and compared using the bearing data named FEMTO which was provided by the FEMTO-ST institute for IEEE 2012 PHM Data Challenge competition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.1-7
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• 2016

Although the second driving device of KTX, which consists of the wheel and the axle reduction gears unit, is a mechanically integrated structure, its preventive maintenance (PM) requires two separate intervals due to the different technical requirements. In particular, these subsystems perform attaching and detaching work simultaneously according to the maintenance directive. Therefore, to reduce the unnecessary amount of PM and high logistic availability of the train, it is important to optimize PM with regard to reliability-centered maintenance toward a cost-effective solution. In this study, fault tree analysis and reliability of the subsystems, considering the criticality of the components, were performed using the data derived from field data in maintenance. The cost optimization of the PM was derived from a genetic algorithm considering the target reliability and improvement factor. The cost optimization was derived from a maximum of the fitness function of the individual in generation. The optimal TBO of them using the genetic algorithm was 2.85x106 km, which is reduced to approximately 21% compared to the conventional method.