• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1759-1766
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• 2001

Vibration transient generated by developing localized fault in gear can be used as indicators in gear fault detection. In this paper, we propose the zoomed phase map for a fault signal using continuous wavelet transfers to detect this vibration transient. Local fault induces the abrupt fluctuation of load exciting tooth and phase lag in the vibration signal measured on the gearbox. The relatively large fault like "tip breakage" easily can be detected by the clear fluctuation of exciting load. However, minor fault like "initial pitting"cannot be detected using the load fluctuation. To defect this kind of minor fault, the phase map for a fault signal is taken into account. The phase lag by minor fault is observed well in the zoomed phase map.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.2
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• pp.253-259
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• 2006

There is few study which automatically diagnoses the fault from ship's monitored data. The bigger control and monitoring system is. the more important fault diagnosis and maintenance is to reduce damage caused by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault from monitored data and is composed of fault detection knowledge base and fault diagnosis knowledge base. For all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem, To verify capability of fault detection, diagnosis and prediction, FMS(Fault Management System) is developed by C++. Simulation by FMS is carried out with population data set made by the log book data of 2 months duration from a large full container ship of H shipping company.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.251-256
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• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.997-1004
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• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1113-1118
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• 2018

Protection in HVDC(High Voltage Direct Current) have the very fast velocity of fault detection. Because Fault in HVDC has the fast propagation, large currents, high interruption cost. The focus to velocity caused possibility of errors like a detection error like a high impedance fault. In this paper, Proposed complex composition for get the reliability and velocity. That used SFCL(Super Conducting Fault Current Limiter), Protection Zone and DTS(Distributed Temperature Sensing). The SFCL was detect the fault by quench and DTS&Protection Zone were perceive the detect by variation too. To examine the proposed method, PSCAD/EMTDC simulated. The results of simulation, proposed methods could the detect of fault to whole HVDC line. And that improved the reliability of fault clearing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1442-1449
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• 2016

This paper proposes a diagnosis to detecting poor contact fault and fault location. Electrical fire by poor contact fault of power cable occupied a large proportion in the total electrical installations. The proposed method has an object to prevent electrical fault in advance. But detecting poor contact fault is difficult to detect fault type and fault location by using conventional reflectometry due to faults generated intermittently and repeatedly on the time change. Therefore, in this paper poor contact fault and fault conditions were defined. System generating poor contact fault produced for the experimental setup. SSTDR and algorithm of reference signal elimination heighten performance detecting poor contact fault on live power cable. The diagnosis methods of signal process and analysis of reflected signal was proposed for detecting poor contact fault and fault location. The poor contact fault and location had been detected through proposed diagnosis methods. The fault location and error rate of detection were verified detecting accuracy by experiment results.

• Journal of Computing Science and Engineering
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• v.9 no.3
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• pp.142-154
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• 2015

Fault localization techniques help locate faults in source codes by exploiting collected test information and have shown promising results. To precisely locate faults, the techniques require a large number of test cases that sufficiently exercise the executable statements together with the label information of each test case as a failure or a success. However, during the process of software development, developers may not have high-coverage test cases to effectively locate faults. With the test case generation techniques, a large number of test cases without expected outputs can be automatically generated. Whereas the execution results for generated test cases need to be inspected by developers, which brings much manual effort and potentially hampers fault-localization effectiveness. To address this problem, this paper presents a method to select a few test cases from a number of test cases without expected outputs for result inspection, and in the meantime selected test cases can still support effective fault localization. The experimental results show that our approach can significantly reduce the number of test cases that need to be inspected by developers and the effectiveness of fault localization techniques is close to that of whole test cases.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.100-106
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• 2015

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This quantification generates fault tree solutions such as minimal cut sets, minimal path sets, or binary decision diagrams (BDDs), and then, calculates top event probability and importance measures. This paper presents a new linear time algorithm to detect modules of large fault trees. It is shown through benchmark tests that the new method proposed in this study can very quickly detect the modules of a huge fault tree. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

• International Journal of Safety
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• v.11 no.2
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• pp.22-25
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• 2012

This paper deals with the problem of fault diagnosis for identifying a single fault when the number of assumed faults is larger than that of predictive variables. Principal component analysis (PCA) is employed to isolate and identify a single fault. PCA is a method to extract important information as reducing the number of large dimension in a process. The patterns of all assumed faults can be recognized by PCA and these can be employed whether a new fault is one of predefined faults or not. Through PCA, empirical models for analyzing patterns can be trained. When a single fault occurs, the pattern generated by PCA can be obtained and this is used to identify a fault. The performance of the proposed approach is illustrated in the actuator benchmark problem.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.74-81
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• 2004

In this study, static end loading tests with load transfer measurement were accomplished for large diameter drilled shaft constructed in fault zone. Yield pile capacity (or ultimate pile capacity) from load-settlement curve was determined and axial load transfer behavior was measurd. The end bearing capacity was increased 2 times due to grouting the toe ground under pile base.