• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.54-57
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• 2003

본 논문에서는 멀티웨이브릿 변환영역에서 통계적 모델과 지각적 동조특성을 이용한 적응적 디지털 워터마킹 기법을 제안한다. 워터마크는 4레벨로 분해된 멀티웨이브릿 변환영역에서 최저주파 영역과 최고주파 대역들을 제외한 중간 및 고주파 영역에, 인간 시각 시스템(human visual model BWS)을 이용한 JND(just noticeable difference) 특성과 NVF(noise visibility function)를 이용한 통계적 특성을 기반으로 정상상태 가우시안 모델과 비정상상태 가우시안 모델에 따라 지각적 동조 특성을 이용하여 적응적으로 삽입된다. 실험 결과 제안한 방법에서 에지나 텍스쳐 영역에 더 강하게 삽입할 수 있었고, 평탄영역에서 보다 적응적으로 은닉할 수 있었으며 정상상태 가우시안 모델에서 지각적 동조특성을 이용한 방법이 더 우수한 비가시성과 강인성을 확인하였다.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.101-105
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• 2018

In this paper, the kernel regression model is applied for the case study of gas turbine abnormal state analysis. In addition to vibration analysis at the remote site, the kernel regression model technique can is useful for analyzing abnormal state of rotor vibration signals of gas turbine in power plant. In monitoring based on data-driven techniques correlated measurements, the fault free training data of shaft vibration obtained during normal operations of gas turbine are used to develop a empirical model based on auto-associative kernel regression. This data-driven model can be used to predict virtual measurements, which are compared with real-time data, generating residuals. Any faults in the system may cause statistically abnormal changes in these residuals and could be detected. As the result, the kernel regression model provides information that can distinguish anomalies such as sensor failure in a shaft vibration signal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.296-302
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• 2021

This paper proposes an approach to the classification of respiratory states of humans based on visual information. An ultra-wide-band radar sensor acquired respiration signals, and the respiratory states were classified based on two-dimensional (2D) images instead of one-dimensional (1D) vectors. The 1D vector-based classification of respiratory states has limitations in cases of various types of normal respiration. The deep neural network model was employed for the classification, and the model learned the 2D images of respiration signals. Conventional classification methods use the value of the quantified respiration values or a variation of them based on regression or deep learning techniques. This paper used 2D images of the respiration signals, and the accuracy of the classification showed a 10% improvement compared to the method based on a 1D vector representation of the respiration signals. In the classification experiment, the respiration states were categorized into three classes, normal-1, normal-2, and abnormal respiration.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.12
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• pp.1351-1358
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• 2011

To approximate the threshold of the fault detection and diagnosis (FDD) system, validation of the measurements is mandatory. Naturally, the system shows uncertainties due to measuring sensors - mostly thermocouples or RTDs - and due to repeatability. The uncertainty of a thermocouple comes from natural variation or a drift of the thermocouple measurement. Considering the natural variation behaves like zero-mean white noise, its natural variation can be characterized closely by the steady-state standard deviation. However, residuals between measurements and no-fault references in FDD systems show a statistical distribution with various uncertainties. In this paper, steady-state variations of measurement residuals were investigated by utilizing built-in temperature sensors in a heat pump for the model development and the final application.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1994.11a
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• pp.150-154
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• 1994

본 연구는 원자력발전소용 시뮬레이션 언어인 DSNP 언어를 이용하여 CANDU-6 발전소 운전 모사 프로그램을 구성함으로써 핵심계통인 1차냉각재 계통(PHTS)과 2차 계통 일부가 정상 및 과도조건에서 보일 수 있는 운전 상태를 연구하였다. DSNP 프로그램은 원자로심과 증기발생기에서의 열전달 모델, 열수송계통 펌프 모델 및 가압기 열수력 모델을 포함하고 있으며, 파이프(pipe)라는 단위 구성체를 이용하여 1차 냉각재계통을 노드화하여 계통 모사가 실현된다. 정상상태 100% 전출력 운전시 대표적인 운전변수를 기준으로 DSNP 결과와 CANDU-6 발전소 설계치를 비교해본 결과 서로 매우 근사한 값을 나타내었으며, 이는 과도상태 모사의 초기조건으로 합당한 것으로 판단된다. 본 연구에서 선택된 과도상태 모사시 DSNP 프로그램은 매우 안정된 '최종정상상태'를 얻음에 따라 원자로의 기계 물리학적 변화를 합리적으로 모사하고 있음을 알 수 있었다. CANDU-6 단계감발 운전시 동적 거동을 원자로 설계자료인 '예비 안전성 평가 보고서(PSAR)'와 비교한 결과 단기적 거동은 PSAR 결과와 다소 다른 점이 있었으나 전체적으로 합리적인 운전변수 값을 얻을 수 있었다. 단기적 거동에 대한 입증은 원자로 운전자료를 통하여 가능할 것으로 사료된다. 이상과 같이 본 연구를 통해 구성한 DSNP 프로그램은 보완 및 개선의 여지가 있으나 현재의 수준으로도 CANDU-6 발전소의 일부 과도상태 모사가 가능한 것으로 판단된다

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.229-230
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• 2015

본 논문은 전력계통 과도안정도 해석에서 많이 쓰이고 있는 가스터빈 모델인 GAST 모델과 GAST2A 모델에 대해서 과도안정도 관점에서 모의 비교한다. 두 가스터빈 모델은 1기 무한모선으로 계통을 구성하여 정상상태에서 조속기 10% 스텝응동 특성을 모의하여 서로 응동특성이 같도록 모델정수를 튜닝하였다. 그리고 발전단에 150 ms 3상 단락사고를 발생시켜 과도상태 특성을 비교하였다. 3상 단락사고인 경우 배기가스 온도제한이 없는 정상 출력상태인 경우와 온도제한 제어특성이 활성화 되는 출력인 경우를 상정하여 비교 분석하였다.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.121-129
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• 2008

Major factors affecting water quality in rivers are transportation, input of pollutant loads and kinetic transformation of pollutants. Government level decision makings on water quality management are based on steady state water quality modeling. However, it is more than often that such a steady state assumption is far from real situations in rivers. Therefore, it is unavoidable to have modeling errors in water quality modeling especially for steady state modeling for longer period of time. Authors attempted to identify sources of errors in results of steady state models and thus tried to find out ways to minimize those errors. Three water quality models, QUAL2E (Brown et al., 1983), QUAL2K (Chapra et al., 2006) and CAP (Seo and Lee, 2000) were applied to the lower stream of the Geum River. $BOD_5$ and COD tend to underestimate observed data while TN and TP showed relatively smaller errors. QUAL2E model provided best calibration results for BOD5 and TP and QUAL2K model showed best calibration results for TN. Since these errors are only relative values, it was difficult to conclude which model is better performing in certain situations. The most probable reasons for errors in water quality modeling are; 1) inappropriate consideration on flow characteristics, 2) lack of information on incoming pollutant load and 3) inappropriate location of sampling for water quality analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.357-365
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• 2022

Refrigerant mischarging is one of the most frequently occurring failure modes in air conditioners, and both undercharging and overcharging degrade cooling performance. Therefore, it is important to accurately determine the amount of charged refrigerant. In this study, a support vector machine (SVM) model was developed to multi-classify the refrigerant mischarge through steady-state identification via fuzzy clustering techniques. For steady-state identification, a fuzzy clustering algorithm was applied to the air conditioner operation data using the difference between moving averages. The identification results using the proposed method were compared with those using existing steady-state determination techniques studied through the inversed Fisher's discriminant ratio (IFDR). Subsequently, the main features were selected using minimum redundancy maximum relevance (mRMR) considering the correlation among candidate features, and an SVM multi-classification model was devised using the derived features. The proposed method achieves satisfactory accuracy and robustness from test data collected in the new domain.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2001.11a
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• pp.57-62
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• 2001

본 연구에서는 검증된 BSU 3톤/일급 석탄가스화공정에 대해 개발된 동적모델을 폐유가스화 공정모텔에 적용하였다. 대상공정에 포함된 조작변수들의 변동에 따른 주요 공정변수인 산소/폐유비를 3% 계단증가시킨 결과, 폐유가스화기의 압력은 15분의 시상수를 보이며 최종적으로 2.4%가 증가된 정상상태에 도달하였고, 온도는 초기 1분 이내에 약 3.2%의 급격한 증가를 보인 후 최종적으로 4.1% 증가된 정상상태에 도달하였다. 그리고 생성가스의 조성은 이산화탄소가 6% 증가되었고, 일산화탄소와 수소는 각각 2% 및 8% 감소된 새로운 정상상태에 도달하였다. 이러한 결과를 토대로 폐유가스화기의 부하변동에 따른 주요 공정변수들의 변동경향 및 신뢰성 있는 동적모사 결과를 얻고, 개발된 모델에 cascade 및 ratio 방식의온도, 압력 제어로직을 설계하여 실공정 적용실험을 통한 전산모사결과 및 안정된 운전특성을 검증할 수 있는 기초를 마련하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.5
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• pp.477-483
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• 2015

In this paper, Euler-Bernoulli beam theories(EB-beam) are used, and Fast Fourier Transformation(FFT) analysis is then employed to extract their natural frequencies using both analytical approach and Co-rotational plane beam(CR-beam) EDISON program. EB-beam is used to analyze a spring-mass system with a single degree of freedom. Sinusoidal force with various frequencies and constant magnitude are applied to tip of each beam. After the oscillatory tip response is observed in EB-beam, it decreases and finally converges to the so-called 'steady-state.' The decreasing rate of the tip deflection with respect to time is reduced when the forcing frequency is increased. Although the tip deflection is found to be independent of the excitation frequency, it turns out that time to reach the steady state response is dependent on the forcing frequency.