• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.19-26
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• 2005

There are three reasoning method in fault diagnosis process. The shallow reasoning is based on the experiential knowledge and deep reasoning is based on physical model. Hybrid reasoning is mixing two type reasoning. This study describes about fault train embodiment of screw type air compressor that is used widely in industrial facilities by using various experimental method and shallow reasoning. We investigate macroscopic failure cause of air compressor through naked eye observation and then microscopic failure cause by various experimental method. We composed fault train with fault knowledge based on empirical data and scientific data that is acquired through several experiments. It is possible to analysis system reliability and failure rate with these fault train.

• Proceedings of the KSR Conference
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• 2000.05a
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• pp.188-194
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• 2000

This study is about fault detection and fault area detection of LV circuit in Cab Cubicle system which have control of train to keep safety in High Speed Train. LV circuit is operated with diagnosis system like safety system. In this paper, we suggest a design and an implementation method to detect fault or to detect fault area automatically about LV circuit. The implemented system is tested successfully after implementation of some function. We expect reduction to diagnosis area or repair time by fault area module

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.859-866
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• 2001

Recently, fault injection techniques are used for evaluation of the fault coverage properties of safety-critical systems. This paper describes the TCN Fault Injector(TFI) implemented for TCN safety analysis. The implemented TFI injects network level faults to Intelligent MVB Controller that is designed for the Korean High Speed Train. With TFI, it can be verified whether the MVB controller meets TCN specification and its safety requirements.

• Proceedings of the KIEE Conference
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• summer
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• pp.307-309
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• 2004

A DC railway system has low feeder voltage, The remote fault current can be smaller than the current of load starting. So it is important to discriminate between the small fault current and the train starting current. The train starting current increases step by step but the fault current increases all at once. So the type of $\bigtriangleup I\;relay(50F)$ was developed using the different characteristics between the load starting current and the fault current. As for the train starting current, the time constant of train current at each step is much smaller than that of the fault current. To detect faults in U railway systems, an algorithm that is independent of train starting current. This algorithm use the time constant calculated by the method of least squares is presented in this paper.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.176-186
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• 2015

Pattern classifications have become important tools for fault diagnosis in nuclear power plants (NPP). However, it is often difficult to obtain training data under fault conditions to train a supervised classification model. By contrast, normal plant operating data can be easily made available through increased deployment of supervisory, control, and data acquisition systems. Such data can also be used to train classification models to improve the performance of fault diagnosis scheme. In this paper, a fault diagnosis scheme based on semisupervised classification (SSC) scheme is developed. In this scheme, new measurements collected from the plant are integrated with data observed under fault conditions to train the SSC models. The trained models are subsequently applied to new measurements for fault diagnosis. In comparison with supervised classifiers, the proposed scheme requires significantly fewer data collected under fault conditions to train the classifier. The developed scheme has been validated using different fault scenarios on a desktop NPP simulator as well as on a physical NPP simulator using a graph-based SSC algorithm. All the considered faults have been successfully diagnosed. The results have demonstrated that SSC is a promising tool for fault diagnosis in NPPs.

• Journal of the Korean Society for Railway
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• v.10 no.1 s.38
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• pp.88-95
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• 2007

TCN(Train Communication Network) adopts the master/slave protocol to implement real-time communication. In this network, a fault on the master node, cased by either hardware or software failure, makes the entire communication impossible over TCN. To reduce fault detection and recovery time, this paper propose the contention based mastership transfer algorithm. Slave nodes detect the fault of master node and search next master node using the proposed algorithm. This paper also shows the implementation results of a SoC-based Fault-Tolerant MVB Controller(FT-MVBC) which includes the fault-detect-logic as well as the MVB network logic to verify this algorithm.

• Journal of KSNVE
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• v.8 no.5
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• pp.929-935
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• 1998

Safety diagnosis of electric train driving system is performed using vibration signals of running electric train. Safety diagnosis is tried on the viewpoints of the appreciation of superannuation and the fault diagnosis of motor, reduction gear and bogie. The appreciation of superannuation is checked by the vibration levels of driving parts and the fault diagnosis is done by analyzing the frequencies of the vibration signals which are measured directly from a running electric train. The results shows that the vibration levels of each parts increase as the train gets older and each parts have their own frequency patterns of the vibration. Vibration propagation path is also investigated using calculated the coherence value between bogie and driving system. As the results, it is known that vibration signal can be utilized successfully for the safety diagnosis of the driving part of electric train.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.272-273
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• 2015

This paper analyze scenario of feeder wire fault that occurs in the AC feeding system considering train position. The fault location of AC feeding system is calculated by measuring impedance. However, in this way, estimation error can be occurred because of tie connection, boosting current, etc. Therefore, it's hard to find fault location, so that it is required to detailed circuit analysis according to fault location. We analyze the short circuit impedance values with respect to feeder wire fault according to a train position. In this paper, PSCAD is used for modeling and analysis of AC railway feeding system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2203-2206
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• 2005

A load flow and short circuit fault simulation of AC electrified railway distribution systems is presented with DIgSILENT PowerFactory software. Load flow of electrified railways distribution system with concerning multi train lines and dynamic characteristics of train load is studied for different time laps. The dynamic characteristics of train load in starting and braking conditions with different starting and stopping times and its moving positions makes the load flow complicated so there is a great need in studying the effects of electrified railways on load flow. Short circuit fault transients is also studied and simulated for both power system or traction distribution system and their effects on the operation of the train sets is investigated.

• Journal of Magnetics
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• v.21 no.3
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• pp.413-420
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• 2016

The permanent magnet synchronous motor has high efficiency driving performance and high power density output characteristics compared with other motors. In addition, it has good regenerative operation characteristics during braking and deceleration driving condition. For this reason, permanent magnet synchronous motor is generally applied as a power train motor for electrical vehicle. In permanent magnet synchronous motor, the most probable causes of fault are demagnetization of rotor's permanent magnet and short of stator winding turn. Therefore, the demagnetization fault of permanent magnet and turn fault of stator winding should be detected quickly to reduce the risk of accident and to prevent the progress of breakdown of power train system. In this paper, the fault diagnosis method using high frequency low voltage injection was suggested to diagnose the demagnetization fault of rotor permanent magnet and the turn fault of stator winding. The proposed fault diagnosis method can be used to check the faults of permanent magnet synchronous motor during system check-up process at vehicle starting and idling stop mode. The feasibility and usefulness of the proposed method were verified by the finite element analysis.