• Journal of Aerospace System Engineering
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• v.10 no.4
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• pp.67-74
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• 2016

The primary aim for using a Korean Condition Based Maintenance (CBM) system is to maintain military operational readiness using Interactive Collection Analysis Systems (ICAS) installed on naval vessels. Other aims are to preemptively provision maintenance and supply functions, to guarantee economical management of logistical assets, and to implement data driven equipment life cycle management. In order to accomplish these aims, it is necessary to establish standard system conditions. However, because manufacturers do not provide the technology necessary for maintenance management, it is required to retain component performance maps for each piece of equipment, and to accumulate data about frequently occurring fault patterns. This study confirms the validity of component performance maps using micro gas turbines and provides accumulated data on machine break downs. This would allow real time equipment performance checks and present performance trends. Then analysis would provide solutions for maintaining the best machine operating conditions with detailed maintenance manuals for operators. This study is a basis for further research to investigate additional ways to develop CBM using data obtained from naval vessels used in actual military operations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2450-2456
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• 2015

In this paper, we propose a real-time remote monitoring system for distributed solar power generation system. The proposed system consists of PVC, UTC, OTC and monitoring server. PVC collects the operational information from the PV's inverter via serial interface. The sensing data is transmitted to the server by wireless communications and stored in the DB server. The PV's status is monitored via UTC, and the operating of PVC and UTC are managed by OTC. In addition, by providing information about the power generated by PV system and failure diagnosis in real time, the proposed system shows the possibility of reducing the maintenance costs and improved failure recovery time.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1867-1879
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• 1997

DREAM-S is a distributed main-memory database system for the real-time processing of shared operational datra in ATM switching systems. DREAM-S has a client-server architecture in which only the server has the diskstorage, and provides the T-Tree index structure for efficient accesses to the data. We propose a recovery technique for the T-Tree index structre in DREAM-S. Although main-memory database system offer efficient access performance, the database int he main-memory may be broken when system failure such as database transaction failure or power failure occurs. Therfore, a recovery technique that recovers the database (including index structures) is essential for fault tolerant ATM switching systems. Proposed recovery technique relieves the bottleneck of the server processors disk operations by maintaining the T-Tree index structure only in the main-memory. In addition, fast recovery is guaranteed even in large number of client systems since the T-Tree index structure(s) in each system can be recovered cncurrently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.90-96
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• 2020

In this era, intelligence is considered a major factor in the defense sector. As a result, securing technology for weapons systems for monitoring and reconnaissance of companies has become inevitable. As a result, UAVs (Unmanned Aerial Vehicles) have been developed and are actively operating around the world if the flight operation of manned aircraft is restricted, such as in environments that are too dangerous, messy or boring for the military to perform directly. The system of unmanned aerial vehicles, which has been researched and developed in Korea, includes Air Vehicle Test Equipment(AVTE). AVTE is equipment that is connected to an UAV to check its status and allows the operator to check its flightability by issuing an operational command to the UAV and verifying that it follows the command values. This study conducts fault finding on the phenomenon where the AVTE has stopped operating due to engine noise during these operations and analyzes the cause in terms of software, hardware and external environment. Present improvement measures according to the cause are analyzed and the results of verifying that the proposed measures can prevent failure are addressed.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.77-84
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• 2002

An cluster system used consist of large number of running servers, one has the problem that does the low availability occured by the high chance of the server failures and it is difficult to provide occuring software aging. In this paper, running cluster web servers consists of n primary servers and k backup servers, based on the operational parameters such as number of running primary servers, number of backup severs, rejuvenation period, rejuvenation time, failure rate of sewers, repair rate of servers, unstable rate of servers. We calculate to evaluate the rejuvenation policy such steady-state probabilities, downtime, availability, and downtime cost. We validate the solutions of mathematical model by experiments based on various operation parameters and find that the software rejuvenation method can be adopted as prventive fault tolerant technique for stability of system. The failure rate and unstable rate of the servers are essential factors for decision making of the rejuvenation policies.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.518-523
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• 2008

Using network communication, KTX OBCS is KTX's core device which inspects operation status of various electric equipments and supports driving command, train control, train's maintenance, train crew's driving. Since this device is manufactured as specialized system, being dependent on TGV manufacture specification and France's high speed train operation method, actual technic transfer is difficult. Therefore, there are many difficulties, since most of interface signals are connected with OBCS when function improvement, maintenance, various electric equipments(propulsion control device, auxiliary power supply device, door control device etc.) are replaced with localized ones, which are required in operational view after introduction of KTX. Ergo, this study would like to contribute to function improvement and maintenance's efficiency, furthermore to realize technical independence, escaping from dependency of developed foreign technology in high speed train and electric equipments, through KTX OBCS' function analysis and mutual interface information analysis with peripheral device(driver console, PID system, fault display device, various electric equipments).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.320-326
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• 2021

AVTE(Air Vehicle Test Equipment) is an equipment to inspect and check the status of on-board aircraft LRUs(Line Replacement Units) before and after flight for performing successful UAV(Unmanned Aerial Vehicle) missions. This paper suggests utilization of the AVTE as an operation support-equipment by implementing several critical functions for UAV-operation on the AVTE. The AVTE easily sets initialization(default) data and compensates for the installation and position errors of the LRUs which provide critical mission data and situation image with pilots without additional individual operation support-equipment. Major fault list and situation image data could be downloaded after flight using the AVTE in the event of UAV emergency situation or unusual occurrence on duty as well. We anticipate the suggested operational approach of the AVTE could dramatically reduce the cost and man power for design and manufacture of additional operation support equipment and effectively diminish workload of the operator.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.273-279
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• 2021

A flight control computer(FLCC) applied to an unmanned aerial vehicle(UAV) is a safety-critical item, and which is designed in a multiple structure to increase the reliability of operation by securing fault tolerance. These FLCC of multiple structure should be designed so that each independent processing/control components can perform the same operation at the same time. And for this reason, a synchronization algorithm for synchronizing the operation between FLCCs should be included in an operational flight program. In this paper, we propose a software design method for synchronization between dual FLCCs applied to UAVs. The proposed synchronization method is designed to synchronize using only the minimum hardware resources to reduce a failure rate. In addition, the proposed synchronization method is designed to minimized synchronization errors due to a timer operation by designing in consideration of operation characteristics of the hardware timer used for the synchronization.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.