• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.760-765
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• 2013

An Interline Power Flow Controller (IPFC) is a converter based controller which compensates and balance the power flow among multi-lines within the same corridor of the multi-line subsystem. The Interline Power Flow Controller consists of a voltage source converter based Flexible AC Transmission System (FACTS) controller for series compensation. The reactive voltage injected by individual Voltage Source Converter (VSC) can be controlled to regulate active power flow in the respective line in which one VSC regulates the DC voltage, the other one controls the reactive power flows in the lines by injecting series active voltage. In this paper, a circuit model for IPFC is developed and simulation of interline power flow controller is done using the proposed circuit model. Simulation is done using MATLAB Simulink and PSPICE. The results obtained by MATLAB are compared with the results obtained by PSPICE and compared with theoretical values.

• Korean Chemical Engineering Research
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• v.50 no.6
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• pp.980-987
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• 2012

Nonpoint source pollution causes leaks and overtopping, depending on the state of the sewer network as well as aggravates the pollution load of the aqueous water system as it is introduced into the sewer by wash-off. According, the need for efficient sewer monitoring system which can manage the sewage flowrate, water quality, inflow/infiltration and overflow has increased for sewer maintenance and the prevention of environmental pollution. However, the sewer monitoring is not easy since the sewer network is built in underground with the complex nature of its structure and connections. Sewer decontamination mechanism as well as pipe network monitoring and fault diagnosis of water network system on system analysis proposed in this study. First, the pollution removal pattern and behavior of contaminants in the sewer pipe network is analyzed by using sewer process simulation program, stormwater & wastewater management model for expert (XP-SWMM). Second, the sewer network fault diagnosis was performed using the multivariate statistical monitoring to monitor water quality in the sewer and detect the sewer leakage and burst. Sewer decontamination mechanism analysis with static and dynamic state system results showed that loads of total nitrogen (TN) and total phosphorous (TP) during rainfall are greatly increased than non-rainfall, which will aggravate the pollution load of the water system. Accordingly, the sewer outflow in pipe network is analyzed due to the increased flow and inflow of pollutant concentration caused by rainfall. The proposed sewer network monitoring and fault diagnosis technique can be used effectively for the nonpoint source pollution management of the urban watershed as well as continuous monitoring system.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.31-37
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• 2021

As the size of buildings increases due to urbanization due to the development of industry, the need to purify the air and maintain a comfortable indoor environment is also increasing. With the development of monitoring technology for refrigeration systems, it has become possible to manage the amount of electricity consumed in buildings. In particular, refrigeration systems account for about 40% of power consumption in commercial buildings. Therefore, in order to develop the refrigeration system failure diagnosis algorithm in this study, the purpose of this study was to understand the structure of the refrigeration system, collect and analyze data generated during the operation of the refrigeration system, and quickly detect and classify failure situations with various types and severity . In particular, in order to improve the classification accuracy of failure types that are difficult to classify, a three-step diagnosis and classification algorithm was developed and proposed. A model based on SVM and LGBM was presented as a classification model suitable for each stage after a number of experiments and hyper-parameter optimization process. In this study, the characteristics affecting failure were preserved as much as possible, and all failure types, including refrigerant-related failures, which had been difficult in previous studies, were derived with excellent results.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.53-59
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• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.233-247
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• 2008

Process monitoring technology is able to detect the faults and the process changes which occur in a process unpredictably, which makes it possible to find the reasons of the faults and get rid of them, resulting in a stable process operation, high-quality product. Statistical process monitoring method based on data set has a main merit to be a tool which can easily supervise a process with the statistics and can be used in the analysis of process data if a high quality of data is given. Because a real process has the inherent characteristics of nonlinearity, non-Gaussianity, multiple operation modes, sensor faults and process changes, however, the conventional multivariate statistical process monitoring method results in inefficient results, the degradation of the supervision performances, or often unreliable monitoring results. Because the conventional methods are not easy to properly supervise the process due to their disadvantages, several advanced monitoring methods are developed recently. This review introduces the theories and application results of several remarkable monitoring methods, which are a nonlinear monitoring with kernel principle component analysis (KPCA), an adaptive model for process change, a mixture model for multiple operation modes and a sensor fault detection and reconstruction, in order to tackle the weak points of the conventional methods.

• Proceedings of the KIPE Conference
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• 2017.11a
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• pp.103-104
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• 2017

영구자석 전동기는 전력 밀도가 높고 효율이 좋은 특징으로 견인, 의료, 군사 분야 등 다양한 산업 분야에서 사용되고 있다. 이러한 분야에서 사용되는 전동기 구동 시스템은 높은 신뢰성이 요구되므로 인버터에서 발생하는 전력 반도체 스위치 고장을 빠르게 감지해야한다. 본 논문에서는 제어기 상전압 지령과 추정된 상전압 사이의 오차를 통해 전력 반도체 개방 고장을 감지하고 진단하는 방법을 제시하였다. 제안된 방법은 추가적인 측정 회로 없이 제어기 내부 값을 사용하여 개방 고장을 감지하고 개방된 스위치를 진단할 수 있다. 특히 부하 변동을 고려한 감지 방법을 제안하여 고장 감지의 신뢰성을 개선한다.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.55-65
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• 2019

With the rapid development of the national industry, the importance of electrical safety was recognized because of a lot of new electrical equipment are installing and the electrical accidents have been occurring annually. Today, the electrical equipments is inspect by using the portable Infrared thermal imaging camera. but the most negative element of using the camera is inspected for only state of heating, the reliable diagnosis is depended with inspector's knowledge, and real-time monitoring is impossible. This paper present the infrared thermal imaging safety diagnosis system. This system is able to monitor in real time, predict the state of fault, and diagnose the state with analysis of thermal and power data. The system consists of a main processor, an infrared camera module, the power data acquisition board, and a server. The diagnostic algorithm is based on a mathematical model designed by analyzing the Pearson's Correlation Coefficient between temperature and power data. To test the prediction algorithm, the simulations were performed by damaging the terminals or cables on the switchboard to generate a large amount of heat. Utilizing these simulations, the developed prediction algorithm was verified.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.447-454
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• 2013

A model-based method is proposed to diagnose the gear crack in the gearbox under variable loading condition with the objective to apply it to the wind turbine CMS(Condition Monitoring System). A simple test bed is installed to illustrate the approach, which consists of motors and a pair of spur gears. A crack is imbedded at the tooth root of a gear. Tachometer-based order analysis, being independent on the shaft speed, is employed as a signal processing technique to identify the crack through the impulsive change and the kurtosis. Lumped parameter dynamic model is used to simulate the operation of the test bed. In the model, the parameter related with the crack is inversely estimated by minimizing the difference between the simulated and measured features. In order to illustrate the validation of the method, a simulated signal with a specified parameter is virtually generated from the model, assuming it as the measured signal. Then the parameter is inversely estimated based on the proposed method. The result agrees with the previously specified parameter value, which verifies that the algorithm works successfully. Application to the real crack in the test bed will be addressed in the next study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1324-1343
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• 2014

In recent years, the problem of spectrum mobility in Cognitive Radio (CR) Networks has been widely investigated. In order to utilize spectrum resources completely, many spectrum handoff techniques based on game theory have been proposed, but most studies only concern that users how to achieve better payoffs, without much attention to the diverse needs of users. In this paper, we propose a new channel-switching model based on game theory, using a prioritized approach to meet the diverse needs of users in two different modes (CQ and PS). At the same time, this paper proposes some acceleration techniques to reach the Nash equilibrium more efficiently. We evaluate the performance of the proposed schemes depending on priority using real channel availability measurements, and conclude that the channel quality function (CQ) mode provide better service for priority user but the plan-sorting (PS) mode can be more suitable in multiple priority users exist scene.

• Journal of KSNVE
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• v.11 no.1
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• pp.125-131
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• 2001

There is a clearance between the parts of a machine due to design tolerance, manufacturing error, wear, looseness, or misalignment. If the clearance is large, the vibration and noise of the machine is generally large. Therefore, the analysis on the nitration and noise of a machine can tell the clearance of the machine, which reveals the condition of the machine, i.e., the existence of faults and the safety of the machine. The investigation of this kind of research should be on the basis of experimental results. A link mechanism with a clearance at a joint between the coupler and locker is made for the investigation of the condition monitoring of a machine due to clearance. The vibration and sound are measured from the link driving system during the operation. The signals are clarified using line enhancement technique. The noise removed signals are used to develop the dynamic model of the system for a model based fault diagnosis. Also this study showed that the clarified signals can be used for the calculation of the joint forces between the coupler and rocker and for the correlation between the vibration and sound levels and the clearance sizes.