• 품질경영학회지
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• 제43권4호
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• pp.573-588
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• 2015

Purpose: For improving result of estimated remaining useful life in Prognostics and Health Management (PHM), a system which is able to consider a lot of environment and load data is required. Method: A load profile monitoring system was presented based on cloud computing for gathering and processing raw data which is included environment and load data. Result: Users can access results of load profile information on the Internet. The developed system provides information which consists of distribution of load data, basic statistics, etc. Conclusion: We developed the load profile monitoring system for considering much environment and load data. This system has advantages such as improving accessibility through smart device, reducing cost, and covering various conditions.

• 한국CDE학회논문집
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• 제5권2호
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• pp.175-183
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• 2000

Proposed in this paper is a model-bated AFA (automatic feedrate-adjustment) method for maintaining smooth cutting-loads (i.e., cutting-force) during 2D-profile milling. Before the cutting-force model was established, some assumptions were verified through a series of preliminary cutting experiments (The results found that the curving-force was independent of the cutting speed and the cutting action at the cutter bosom). From the data obtained during the main cutting experiments, a “chip-load/cutting-force model”representing the cutting-force as a function of the chip-load (i.e., effective cutting-depth) and a feedrate is proposed. Based on the model. an AFA scheme for maintaining smooth cutting-force by adjusting the feedrate (i.e., F-code) according to the changes in chip-load was proposed. To check the validity of the proposed AFA scheme. another set of cutting experiments was conducted by using feedrate-adjusted NC-data while monitoring the actual machining processes using an accelerometer. The experimental results showed that the proposed AFA-scheme was quite effective.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.572-580
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• 2013

Power metering and monitoring system is a basic element of Smart Grid technology. This paper proposes a new Non-Intrusive Load Monitoring (NILM) method for a residential buildings sector using the measured total active power consumption. Home electrical appliances are classified by ON/OFF state models, Multi-state models, and Composite models according to their operational characteristics observed by experiments. In order to disaggregate the operation and the power consumption of each model, an algorithm which includes a switching function, a truth table matrix, and a matching process is presented. Typical profiles of each appliances and disaggregation results are shown and classified. To improve the accuracy, a Time Lagging (TL) algorithm and a Permanent-On model (PO) algorithm are additionally proposed. The method is validated as comparing the simulation results to the experimental ones with high accuracy.

• Smart Structures and Systems
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• 제28권6호
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.172-174
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• 2007

An electronic watt-hour meter with high-precision measurement technology can provide many valuable metering data of a real-time system measurements, such as per-phase voltage, ampere, active power, reactive power, apparent power, power factor, and system frequency. Also many of accumulated metering data such as active energy, reactive energy, apparent energy, and load profile can be gettable from an electronic watt-hour meter[1]. This paper presents an approach of the small-sized AMR (Automatic Meter Reading) that provides customers with a very valuable electrical service. This AMR service transmits lots of a valuable metering data by using ZigBee communication module, so that users resided in their premises can use the information to audit a power quality and improve their electrical conditions by using the PQ monitoring device equipped with ZigBee receiver. This PQ monitoring device shows metering data on LCD and transmits to the PC through an internal network. Also, the device can keep the valuable meter data into a built-in non-volatile memory. The final goal of this paper is to better understand the power quality of electrical systems and offer the power qualify information for the convenience of all power consumers.

• 한국항만학회지
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• 제14권4호
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• pp.463-473
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• 2000

Reinforcement with geotextiles have been used in the foundation soil to enhance the resistance of embankments to avoid failure through excessive deformation or shear in the foundation. It is improtant to know the amount of the strain and the displacement of buried geotextiles for the verification of the reinforcement behaviour. Full scale trial constructions were performed to check the deformational characteristics of the polyester(PET) mat which was used for the embankment reinforcement. Many instrumentation equipments including surface settlement plates, profile gauges and inclinometer casings were installed to observe the behaviour of the soft ground due to the soil embankment. 60 electrical resistance strain gauges and 9 vibrating wire LVDTs were installed 세 measure the deformation of the polyester mat. Results of various tests and geotextile, waterproofing and protection from the hazard environments were introduced. The proposed instrumentation method was effective for the monitoring or the geotextile behaviour. The direct attachment of electrical resistance strain gauges on the gertextile mat was able to measure small changes of the strain of geotextiles. At the end of the 5 month monitoring, 54 of 60 (93%) strain gauges and 7 of 9 (78%) displacement transducers survived all perils of the compaction impacts and the humidity. And the tensile strain of grotextiles increased as the ground displacement became larger. Though the observed strain of mats under the 3m high embankment load was less than 1%, the magnitudes of the strain according to the mat spreading method were different from each other.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1828-1829
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• 2011

본 논문에서는 KEPCO가 사업화중인 AMI(Advanced Metering Infrastructure)시스템을 이용하여 변압기 2차 측에서의 전력공급량 측정과 수용가로부터의 전력사용량 수집하고, 상기 전력사용량의 차이를 비교 분석하여 통상적인 전력 손실 및 도전감시를 수행할 수 있는 방법을 소개하고자 한다. 전력 감시모듈은 전원 공급부, 전류 및 전압 감지부, 수집한 전류 및 전압을 이용하여 각종 정보를 생성하는 엔진부 및 데이터 통신부로 구성된다. 전력손실 및 도전감시 방법은 전자식 전력량계가 생성하는 LP(Load Profile)의 15분 기록주기를 기준으로 전력공급량과 전력 사용량을 비교 분석하여 통상적인 전력 손실률을 산출한다.

• Wind and Structures
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• 제3권3호
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• pp.143-158
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• 2000

This report presents the findings of a one-year monitoring effort to empirically characterize and evaluate the nature of near-ground winds for structural engineering purposes. The current wind engineering practice in the United States does not explicitly consider certain important near-ground wind characteristics in typical rough terrain conditions and the possible effect on efficient design of low-rise structures, such as homes and other light-frame buildings that comprise most of the building population. Therefore, near ground wind data was collected for the purpose of comparing actual near-ground wind characteristics to the current U.S. wind engineering practice. The study provides data depicting variability of wind speeds, wind velocity profiles for a major thunderstorm event and a northeaster, and the influence of thunderstorms on annual extreme wind speeds at various heights above ground in a typical rough environment. Data showing the decrease in the power law exponent with increasing wind speed is also presented. It is demonstrated that near-ground wind speeds (i.e., less than 10 m above ground) are likely to be over-estimated in the current design practice by as much as 20 percent which may result in wind load over-estimate of about 50% for low-rise buildings in typical rough terrain. The importance of thunderstorm wind profiles on determination of design wind speeds and building loads (particularly for buildings substantially taller than 10 m) is also discussed. Recommendations are given for possible improvements to the current design practice in the United States with respect to low-rise buildings in rough terrain and for the need to study the impact of thunderstorm gust profile shapes on extreme value wind speed estimates and building loads.

• 한국태양에너지학회 논문집
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• 제40권3호
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• pp.1-20
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• 2020

In accordance with the Government's policy, renewable power generation is expanding very largely. This leads to increasing uncertainty in the power market and power system owing to the intermittent and fluctuating output characteristics of renewable power generators. Data on the acquisition of renewable power generators can be largely classified according to the operation of the power market and power system. Data on the settlement for the payment for the power amount are acquired in the power market, and real-time data for monitoring the status and output of the generators are acquired in the power system. However, renewable power generators operating in the power market have different acquisition cycles depending on the method of communication of the power meter. They acquire data only for settlement purposes and have no real-time data, which requires improvement. In this paper, the acquisition status is reviewed by classifying the data of renewable power generators into settlement and real-time data. In addition, measures and acquisition criteria for real-time data of renewable power generators for improving the acquisition method are proposed.

• KSBB Journal
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• 제25권1호
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• pp.85-90
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• 2010

An ion selective microelectrode (ISME) was fabricated to measure concentrations of ammonium (${NH_4}^+$-N) and nitrate (${NO_3}^-$-N) according to the depth of nitrifying biofilm. The limits of detectability and validity of results were investigated to evaluate the ISME. The electromotive force (EMF) was directly proportional to the ion concentration, and average detection limits of ${NH_4}^+$ and ${NO_3}^-$ ISME were $10^{-5.14}$ and $10^{-5.18}$ M, respectively. The concentrations of ${NH_4}^+ $-N and ${NO_3}^-$-N in various depths on the nitrifying biofilm were measured by the ISME. When a modified Ludzack-Ettinger (MLE) process was operated at an HRT of 6 h, concentration gradients of ${NH_4}^+$-N in the bulk solution and biofilm at depths of $100\;{\mu}m$ decreased by $70\;{\mu}M$, while ${NO_3}^-$-N increased by $101\;{\mu}M$ and remained constant thereafter. At an HRT of 4 h, concentration gradients of ${NH_4}^+$-N at depths of $500\;{\mu}m$ decreased by $160\;{\mu}M$ and ${NO_3}^-$-N increased by $162;{\mu}M$ and remained constant thereafter. As HRT decreased, the concentration gradients of ${NH_4}^+$-N and ${NO_3}^-$-N between bulk solution and biofilm was higher due to the increase of nitrogen load. Also, the concentration gradients of the ${NH_4}^+$-N and ${NO_3}^-$-N of biofilm in the second aerobic tank were lower than those of the first aerobic tank, suggesting differences of nitrogen load and concentrations of DO between the first and second aerobic tank.