• Journal of the Korean Society of Safety
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• v.21 no.1 s.73
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• pp.6-14
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• 2006

The development of automatic production systems have required intelligent diagnostic and monitoring functions to overcome system failure and reduce production loss by the failure. In order to perform accurate operations of the intelligent system, implication about total system failure and fault analysis due to each mechanical component failures are required. Also solutions for repair and maintenance can be suggested from these analysis results. As an essential component of a mechanical system, a bearing system is investigated to define the failure behavior. The bearing failure is caused by lubricant system failure, metallurgical deficiency, mechanical condition(vibration, overloading, misalignment) and environmental effects. This study described slab transfer equipment fault train due to stress variation and metallurgical deficiency from lubricant failure by using FTA.

• Journal of the Korea Safety Management & Science
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• v.3 no.2
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• pp.113-121
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• 2001

Today, facilities are composed of many complex components or parts. Because of this characteristics, the frequency of failures is decreasing, but the strength of failures is increasing; therefore, the failure analysis about many complex components or parts was needed. In the former research about Fault Tree Analysis, failure data of similar facilities have been used for forecasting about target system or components, but in case that the system or components for forecasting failure is new or qualitative and quantitative data are given simultaneously, there are many difficulty in using Fault Tree Analysis with this incorrect failure data. Therefore, this paper deal with the Fault Tree Analysis method which be applied with Fuzzy theory in above case. In case that , therefore, if there is no the correct failure data, it is represented a system or components as qualitative variable. subsequently, it converted to the quantitative value using fuzzy theory, and the values used as the value for failure forecast.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.7
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• pp.309-316
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• 2005

In this paper we analyzed a dangerous failure and a safety requirement based on HIA (Hazard Identification and Analysis) of an interface model between CTC (Centralized Traffic Control) system and El (Interlocking) system, and assigned SU (Safety Integrity Level) by way of an risk estimation of the interface, which employed PHA (Preliminary Hazard Analysis) for the interface of the track control system, being managed as separated system between the centralized traffic control system and the interlocking system, An estimation which satisfies a safety reference of the international standard has been achieved through a quantification of the system failure rate and the dangerous failure rate of the interface model.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.386-390
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• 2007

At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.125-133
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• 2016

Purpose: The purpose of this study is to evaluate durability of platform safety step system in railway. Method: We performed finite element analysis & durability analysis of platform safety step system with VPD (Virtual Product Development) techniques and examined the durability standard & qualification life through the rig test during no failure test time in reliability qualification test. We continued to test 1 million cycles in KRS (Korea Railway Standard) for system's robust design performance. Result: FEM analysis results are 14.9MPa & 14.7MPa of pin-joint, pivot and durability analysis result is above 1 million cycles. we calculated theoretically no failure test time 855,000 cycles and through the 1 million cycles durability rig test in KRS standard we confirmed product quality. Conclusion: This platform safety step system was designed very safe in terms of a mechanical strength & durability.

• Journal of the Korean Society of Safety
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• v.29 no.3
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• pp.136-142
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• 2014

Recently a new version of PRO-LOCA program was released. Using the program, failure probability of pipes can be evaluated considering fatigue and/or stress corrosion crack growth and the effects of various parameters on the integrity of pipes in nuclear power plants can be evaluated quantitatively. The analysis results can be used to establish an inspection plan and to examine the effects of important parameters in a maintenance plan. In this study, sensitivity analyses were performed using the program for several important parameters including sampling method, initial crack size, number of initial fabrication flaws, operation temperature, inspection interval, operation temperature and nominal applied bending stress. The effect of parameters on the leak and rupture probability of pipes was evaluated due to fatigue or stress corrosion crack growth.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.789-795
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• 2008

Slope stability is affected by various factors. For safety management of slopes, monitoring systems have been widely constructed along railway lines. The representative data from the systems are variations of ground profile such like ground water level and pore water pressure etc. and direct displacement measured by ground clinometer and tension wire sensor. Slopes are mainly effected by rainfall and rainfall causes the decrease of factor of safety(FOS). Because FOS varies linearly by the variation of ground water level and pore pressure, it has a weak point that could not define the time and proper warning sign to secure the safety of the train. In this study, alternative of FOS such as reliability index and probability of failure is applied to slope stability analysis introducing the reliability concept. FOS, reliability index, probability of failure and velocity of probability of failure of the slopes by variation of ground water level are investigated for setting up the specification of safety management of slopes. By executing case study of a slope(ILLO-IMSUNGLI), it is showed to be applied to specification of safety management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.574-582
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• 2018

In systems such as railways, automobiles, and airplanes, system malfunctions may lead to accidents, which often cause serious personal injury and economic loss. In previous studies, failure analysis has been performed, and safety measures derived using the component level information to reduce damage when a failure occurs. However, in functional safety concept, a focus is placed on lowering the frequency of occurrence of failures by performing risks analysis, setting up safety goals, and designing safety functions. Therefore, it is necessary to study how to determine the required safety function that can reduce the failure frequency to the acceptable level. To achieve this, we first studied a failure modeling method using SysML. It was then presented how several alternatives can be assessed to determine the desired safety function by simulating the generated SysML failure models and calculating the ability to reduce the failure frequency. A case study of a railway signaling system was done, demonstrating the effectiveness of the approach. We assessed whether the safety objectives were met for the alternative design of the railway signaling system through M & S. The results can be useful in that it can be applied from the early design phase and allow to choose the appropriate safety function that satisfies safety objectives among various design alternatives.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.51-59
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• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

• Tunnel and Underground Space
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• v.31 no.5
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• pp.360-373
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• 2021

Many sources of uncertainty exist in geotechnical analysis ranging from the material parameters to the sampling and testing techniques. The conventional deterministic stability analysis of a plane failure in rock slope produce a safety factor but not a probability of failure or reliability index. In the conventional slope stability analysis by evaluating the ground uncertainty as an overall safety factor, it is difficult to evaluate the stability of the realistic rock slope in detail. This paper reviews some established probabilistic analysis techniques, such as the MCS, FOSM, PEM, Taylor Series as applied to plane failure of rock slopes in detail. While the Monte - Carlo methods leads to the most accurate calculation of the probability of safety, this method is too time consuming. Therefore, the simplified probability methods could be alternatives to the MCS. In this study, using these simple probability methods, the failure probability estimation of a plane failure in rock slope is presented.