• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.37-46
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• 2005

In Processing many operations based on distributed environment, it is very important to support the reliability of resources. Providers of resources generally adapt the structure of server-replication to support the reliability of services. Tn server side, it maintains replicas. duplicated server objects. In the structure of this replication, service of stable replica is very important. Therefore the structure to diagnosis the fault of such replica is required. In this Paper, we suggested an effective PUSH fault management algorithm based on PUSH monitoring style of CORBAto overcome weak points of the PULL monitoring style of the replication management system in the distributed object system. Outcomes of the suggested PUSH fault monitoring style were better than other system. We confirmed valuable result in the workloads and timeout-rates.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.516-523
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• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3367-3378
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• 1999

ATM technology, which acts as a representative high-speed bandwidth technology, plays an important role in Internet environment. ATM network, supporting QoS(Quality of Service) and various traffic characters in high speed, configures many VPC(Virtual Path Connection)/VCC(Virtual Channel Connection). It is important to guarantee the QoS of each connection and it is necessary for the network manager to search element affecting the QoS of VPC/VCC and to control ATM network correctly. In the paper, the management information of VPC/VCC, that ATM network manager Using the fault notification for ATM switch, we can manage the configuration, fault and performance of ATM network. Thus, we extracted the configuration, fault and performance monitoring item from the ATM-MIB and SNMP M4 Network Element View MIB. And we designed the ATM network configuration, fault and performance management system based on the extracted item.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.5
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• pp.349-357
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• 2022

Since the flight control computer of unmanned aerial vehicle (UAV) is a flight critical equipment, it is necessary to ensure reliability and safety from the development step, and a redundancy-based fault management design is required in order to operate normally even a failure occurs. To reduce cost, weight and power consumption, the dual-redundant flight control system design is considered in UAV. However, there are various restrictions on the fault management design. In this paper, we propose the fault detection and isolation designs for the dual-redundant flight control computer to satisfy the safety requirements of an UAV. In addition, the flight control computer developed by applying the fault management design performed functional tests in the integrated test environment, and after performing FMET in the HILS, its reliability was verified through flight tests.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.960-968
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• 2005

The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2453-2461
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• 2009

Faults caused by medium-voltage customers have been increased and enlarged their portion in total distribution faults even though we have done many efforts. In the previous paper, we suggested the fault prediction model and fault prevention method for these distribution line faults. However we can't directly apply this prediction model in the field. Because we don't have an useful program to predict those customers causing distribution line faults. This paper presents the construction method of data warehouse in ERP system and the program to find customers who cause distribution line faults in medium-voltage customer's electric facility management applying data mining techniques. We expect that this data warehouse and prediction program can effectively reduce faults resulted from medium-voltage customer facility.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.73-83
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• 2006

In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.131-139
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• 1993

The newly proposed model of the future reliability results in earlier fault-fixes having a greater effect than the fault which make the greatest contribution to the overall failure rate tend to show themselves earlier, and so are fixed earlier. The suggested model allows a variety of reliability measures to be calculated. Predictions of total execution time(debugging time) is to achieve a target reliability. This model could also apply to computer-hardware reliability growth resulting from the elimination of design error and fault.