• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.85-91
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• 2021

In our daily life, artificial intelligence performs simple and complicated tasks like us, including operating mobile phones and working at homes and workplaces. Artificial intelligence is used in industrial technology for diagnosing various types of equipment using the machine learning technology. This study presents a fault mode effect analysis (FMEA) of start motors using machine learning and big data. Through multiple data collection, we observed that the primary failure of the start motor was caused by the melting of the magnetic switch inside the start motor causing it to fail. Long-short-term memory (LSTM) was used to diagnose the condition of the magnetic locations, and synthetic data were generated using the synthetic minority oversampling technique (SMOTE). This technique has the advantage of increasing the data accuracy. LSTM can also predict a start motor failure.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.2
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• pp.233-239
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• 2016

In this paper, a maintenance system is developed for LNG-FPSO topside and hullside equipment based CBM (Condition Based Maintenance) methodology. First, the development system defined the PWBS(Product Work Breakdown Structure) of major equipment of LNG-FPSO. Second, the development system developed the failure analysis, economic evaluation for optimal maintenance plan and database systems that save and manage information about equipment, failure mode, failure rate and failure cause. Finally, the verification of the development system was applied to the inlet system of topside and the pump tower system of hullside and the system was confirmed the effectiveness of CBMS(Condition Based Maintenance System).

• 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.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.205_206
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• 2009

Protection system is important part in distribution system. Protection system in power systems can fail either by not responding when they should(failure to operate) or by operating when they should not(false tripping). Customers has dissatisfied that due to the failure of protection system. The reliability of distribution system also has influenced. However, the failure of protection system can reduced by the maintenance. This paper has focused on malfunction of protection system. The approach is based on Markov models.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.81-83
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• 2005

The Reactor Protection System (RPS) is a very important system in a nuclear power plant because the system shuts down the reactor to maintain the reactor core integrity and the reactor coolant system pressure boundary if the plant conditions approach the specified safety limits. This paper describes the unavailability assessment of a digital reactor protection system using the fault tree analysis technique. The fault tree technique can be expressed in terms of combinations of the basic event failures. In this paper, a prediction method of the hardware failure rate is suggested for a digital reactor protection system. and applied to the reactor protection system being developed in Korea.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.105-112
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• 2006

The main function of a reactor protection system is to maintain the reactor core integrity and the reactor coolant system pressure boundary. Generally, the reactor protection system adopts the 2-out-of-m redundant architecture to assure a reliable operation. This paper describes the safety assessment of a digital reactor protection system using the fault tree analysis technique. The fault tree technique can be expressed in terms of combinations of the basic event failures such as the random hardware failures, common cause failures, operator errors, and the fault tolerance mechanisms implemented in the reactor protection system. In this paper, a prediction method of the hardware failure rate is suggested for a digital reactor protection system, and applied to the reactor protection system being developed in Korea to identify design weak points from a safety point of view.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4762-4767
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• 2012

The AF track circuit that detecting train position and transmitting various train control data for DTG to the train on-board is composed of single operation system. If a failure occurs on this system, the driver should be operate the train by manually until the system is restored, because the system cannot control switch machines and signals by automatically. In this process the human error affects to the train delay, collision, derailment and critical safety accident. Therefore, this document has analyzed the effects that each failure mode influences on system and train, and quantified the failure valuation point and class. Basis on this quantified analysis result, MTBF increased and MTTR decreased and failure number also decreased by adopting the independent installation of power supply, the replacement of defected capacitors, the installation of resister cooling system and the improvement of maintenance methods. And the failure factors of AF track circuits were decreased by conducting the preventive maintenance which is a quantitative way of maintenance system by experience.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.47-56
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• 2008

MC(Mission Computer) performs important function in avionics system which tactic data processing, image processing and managing navigation system etc. In general, the fault of SPOF(Single Point Of Failure) in unity system can lead to failure of whole system. It can cause a failure of a mission and also can threaten to the life of the pilot. So, in this paper, we design the HA(Hight-availability) system so that dealing with the failure. And we use HA software like Heartbeat, Fake, DRBD and Bonding to manage HA system. Also we analyze the performance of HA system using the FDT(Fault Detection Time) for fast fault detection and MTTR(Mean Time To Repair) for mission continuity.

• Journal of the Korean Society of Safety
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• v.15 no.4
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• pp.150-156
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• 2000

In this paper, the human error contributions to the system unavailability are calculated and compared to the mechanical failure contributions. The system unavailability is a probability that a system is in the failed state at time t, given that it was the normal state at time zero. It is a function of human errors committed during maintenance and tests, component failure rates, surveillance test intervals, and allowed outage time. The THERP (Technique for Human Error Rate Prediction), generally called "HRA handbook", is used here for evaluating human error rates. This method treats the operator as one of the system components, and human reliability is assessed in the same manner as that of components. Based on the calculation results, the human error contribution to the system unavailability is shown to be more important than the mechanical failure contribution in the example system. It is also demonstrated that this method is very flexible in that it can be applied to any hazardous facilities, such as gas valve stations and chemical process plants.ss plants.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.963-966
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• 1988

This paper describes the development of a prototype expert system, which is designed to analyze loom production efficiency by employing a loom monitoring system. The problem field of the prototype expert system is the loom failure analysis which has a great effect on prouction efficiency, and the characteristic graph in which the loom failure causes are classified and organized, is used in the analysis. The knowledge for characteristic graph is organized, and an effective inference engine- is developed. The developed system is tested and modified using hypothetical loom failure causes, and the feasibility of the expert system application to extend the functions of the loom monitoring system is proved.