• 한국철도학회논문집
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• 제16권3호
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• pp.183-188
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• 2013

철도차량을 유지보수 하는 목적은 열차가 운행하는 동안 고장이 발생하지 않도록 하는 것이다. 최근의 철도차량은 전기전자 부품은 물론 IT기술이 접목되어 주기적인 예방정비 방식으로는 차량고장을 근본적으로 예방할 수 없게 되었다. 따라서 KTX에 RAMS가 적용되어 도입된 이후 코레일에서 도입하는 철도차량은 RAMS를 적용하고 있다. 새로 제작되는 차량은 운행초기 하자보증기간 동안 신뢰성 검증을 하게 되며, 유지보수 과정에서는 RCM 기법을 적용한다. 본 논문에서는 철도차량의 특성 및 운영 환경에 적합한 철도차량 신뢰성유지보수체계인 RCRM(Reliability Centered Rolling stocks Maintenance) 방안을 제시하고자 한다.

• 한국철도학회논문집
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• 제9권5호
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• pp.606-611
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• 2006

This paper presents a procedure and an analysis method to evaluate reliability of the Korea high-speed train. The rolling stock system is divided into 6 sub-systems and each subsystem is classified into sub-assemblies. Functional analysis has been conducted to draw reliability block diagrams for the sub-systems. First, failure rates has been calculated for each sub-assembly from the failure data obtained during commissioning tests. Then a reliability block diagram is used to evaluate the MKBF(Mean Kilometers Before Failure) of the sub-systems. Activities to increase reliability have been carried out throughout the test runs and analysis results show that the reliability of the rolling stock system is gradually growing in time.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.487-497
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• 2008

This paper addresses the Fault Monitoring System developed by Hyundai-Rotem based on the Mil-HDBK-2155 Failure Reporting, Analysis and Corrective Action System. The purpose of a FRACAS is to provide a documented history of any problems, failures, their associated corrective actions as well as detailing how and why each problem arose or failure occurred during the Warranty Period for Rolling Stock delivered by Hyundai-Rotem. The Fault Monitoring System can assess the reliability, availability and maintainability as well as can predict no. of failure at a time which can input to Life Cycle Cost.

• 전기학회논문지P
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• 제64권4호
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• pp.220-230
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• 2015

Rolling stock RAMS is a field of engineering which integrates reliability, availability, maintainability and safety (RAMS) characteristics into an inherent product design property through rolling stock system engineering process. It is implemented to achieve operational objectives successfully, and recently the RAMS has become a rapidly growing engineering discipline because it has a great potential to ensure safety and improve cost effectiveness. However, the Korean rolling stock industry has not yet implemented RAMS management in the rolling stock engineering process, despite the issue having been addressed since the introduction of the KTX. Thus, this paper discusses the processes, methods and techniques for RAMS assessment in three parts. Firstly, it outlines a process of the overall RAMS performance assessment for achieving technical RAMS design criteria. Secondly, it discusses a process for assessing the operational RAM and allocating the RAM. This paper also proposes a model for assessing safety-based risk management, which includes five analytic techniques for identifying the causes and consequences of a system failure. Finally, a case example is provided for the risk assessment of the pneumatic braking device.

• International Journal of Railway
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• 제1권3호
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• pp.89-93
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• 2008

Reliability of onboard power supply systems on rolling stock is a very important issue for the railway operator. While a failure of the HVAC supply results in a loss of comfort for the passengers, a failure of the supply for air compressors or for the traction cooling systems results in towing the train. This is, looking at the required availability of a train, not acceptable. An active redundancy concept for the onboard power supply maximizes the availability of the system. This paper describes such a system under the aspect of $\cdot$ Weight reduction $\cdot$ Continuous operation when changing from normal to redundant operation $\cdot$ Flexibility in train design.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 추계학술대회 논문집
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• pp.1083-1088
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• 2005

As the industrial society develops rapidly, the weight reduction and high strength are demanded gradually. In case of the welded joint for the rolling stock which receives the repeat load, the structural failure can occur easily. However, if the shot peening technique is applied, the durability and the fatigue characteristics of the rolling stock will be improved because the hardness increases and the residual stress is induced. In this study, the fatigue characteristics of shot peened welled joints for the rolling stock was investigated. The crack initiation was examined and hardness was also evaluated. the results show that the fatigue characteristics of welded joints was improved.

• Journal of Information Technology Applications and Management
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• 제29권6호
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• pp.63-80
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• 2022

In this paper, we study structural changes and performance gains in condition-based maintenance process redesign when mobile IoT technology is embedded into urban railway rolling stock. We first develop condition-based maintenance To-Be process model in accordance with the IoT deployment scheme. Secondly, we draw upon theoretical framework of redesign process analysis to develop performance evaluation method suitable to predictive maintenance shift from As-Is ordinary maintenance practice. Subsequently, To-Be process performance evaluations are conducted adopting both the quantitative and qualitative method for time, cost, and dependability dimensions. The results ascertain the considerable benefits captured through detection abnormality prior to actual rolling stock failure occurrence, and details of performance improvements and enhancement of standardization level is revealed. The procedures and results presented in this paper offers useful insights in the fields of IoT economic analysis, condition based maintenance, and business process redesign.

• 지능정보연구
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• 제26권1호
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• pp.47-73
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• 2020

KTX 차량은 수많은 기계, 전기 장치 및 부품들로 구성되어 있는 하나의 시스템으로 차량의 유지보수에는 상당히 많은 전문성과 유지보수 작업자들의 경험을 필요로 한다. 차량 고장발생 시 유지보수자의 지식과 경험에 따라 문제 해결의 시간과 작업의 질적 차이가 발생하며 그에 따른 차량의 가용율이 달라진다. 일반적으로 문제해결은 고장 매뉴얼을 기반으로 하지만 경험이 많고 능숙한 전문가의 경우는 이와 더불어 개인의 노하우를 접목하여 신속하게 진단하고 조치를 취한다. 이러한 지식은 암묵지 형태로 존재하기 때문에 후임자에게 완전히 전수되기 어려우며, 이를 위해 사례기반의 철도차량 전문가시스템을 개발하여 데이터화된 지식으로 바꾸려고 하는 연구들이 있어왔다. 하지만, 간선에 가장 많이 투입되고 있는 KTX 차량에 대한 연구나 텍스트의 특징을 추출하여 유사사례를 검색하는 시스템 개발은 아직 미비하다. 따라서, 본 연구에서는 이러한 차량 유지보수 전문가들의 노하우를 통해 수행된 고장들에 대한 진단과 조치 이력을 문제 해결의 사례로 활용하여 새롭게 발생하는 고장에 대한 조치가이드를 제공하는 지능형 조치지원시스템을 제안하고자 한다. 이를 위하여, 2015년부터 2017년동안 생성된 차량고장 데이터를 수집하여 사례베이스를 구축하였고, 차원축소 기법인 비음수 행렬 인수분해(NMF), 잠재의미분석(LSA), Doc2Vec을 통해 고장의 특징을 추출하여 벡터 간의 코사인 거리를 측정하는 방식으로 유사 사례를 검색하였으며, 위의 알고리즘에 의해 제안된 조치내역들 간 성능을 비교하였다. 분석결과, 고장 내역의 키워드가 적은 경우의 유사 사례 검색과 조치 제안은 코사인 유사도를 직접 적용하는 경우에도 좋은 성능을 낸다는 것을 알 수 있었고 차원 축소 기법들의 성능 비교를 통해 문맥적 의미를 보존하는 차원 축소 방식 중 Doc2Vec을 적용하는 것이 가장 좋은 성능을 나타낸다는 것을 알 수 있었다. 텍스트 마이닝 기술은 여러 분야에서 활용을 위한 연구들이 이루어지고 있는 추세이나, 본 연구에서 활용하고자 하는 분야처럼 전문적인 용어들이 다수이고 데이터에 대한 접근이 제한적인 환경에서 이러한 텍스트 데이터를 활용한 연구는 아직 부족한 실정이다. 본 연구는 이러한 관점에서 키워드 기반의 사례 검색을 보완하고자 텍스트 마이닝 기법을 접목하여 고장의 특징을 추출하는 방식으로 사례를 검색해 조치를 제안하는 지능형 진단시스템을 제시하였다는 데에 의의가 있다. 이를 통해 현장에서 바로 사용 가능한 진단시스템을 단계적으로 개발하는데 기초자료로써 시사점을 제공할 수 있을 것으로 기대한다.

• 산업경영시스템학회지
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• 제40권1호
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.1486-1493
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• 2008

In this paper, we performed analysis and comparison on emergency response action for passengers, drivers, workers and controllers in case of failure occurrence on rail infrastructure and rolling stock. In general, the subjects of emergency response action perform the response action with following emergency response procedures when accidents occurred. In reality, however, no matter how well the subjects are trained, it is hard to follow the emergency response procedures precisely without making any mistakes. As for emergency response action, the most significant factor for the subjects is to follow the emergency response procedures as learned, without any hesitation. In this paper, therefore, we analyzed the emergency response actions that should be performed by passengers and railway workers when emergency accidents occurred. We also examined the communication facilities for emergency response among train, wayside and station in order to provide the emergency reporting system for passenger and the method for cleaning out the accident area.