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가스터빈용 듀얼타입 온도센서의 고장검출을 위한 퍼지로직 기반의 진단 알고리즘 개발
한영복(Young-Bok Han),김성호(Sung-Ho Kim),김변곤(Byon-Gon Kim) 한국전자통신학회 2023 한국전자통신학회 논문지 Vol.18 No.1
최근 신재생에너지 증가로 인하여 가스터빈 발전기는 양질의 전력공급을 위해 일일 기동·정지가 지속되고 있으며 이에 따른 영향으로 고온부품의 수명이 단축되고 고온 측정용 온도센서의 고장발생 빈도가 높아지고 있는 추세이다. 이에 본 연구에서는 가스터빈 제어에 사용되고 있는 듀얼 온도센서가 고장이 났을 경우 센서의 고장을 정확하게 진단하고 체계적으로 검출할 수 있는 퍼지로직 기반의 고장진단 알고리즘을 제안하였으며, 제안된 알고리즘의 유용성 확인을 위해 Matlab/Simulink의 환경에서 다양한 시뮬레이션을 수행함으로 제안된 알고리즘의 유용성을 확인하고자 하였다. Due to the recent increase in new and renewable energy, gas turbine generators start and stop every day to supply high-quality power, and accordingly, the life span of high-temperature parts is shortened and the failure of combustion chamber temperature sensors increases. Therefore, in this study, we proposed a fuzzy logic-based failure diagnosis algorithm that can accurately diagnose and systematically detect the failure of the sensor when the dual temperature sensor used for gas turbine control fails, and to confirm the usefulness of the proposed algorithm We tried to confirm the usefulness of the proposed algorithm by performing various simulations under the matlab/simulink environment
폴리트로픽 지수 기반의 재열 가스터빈 입구온도 산출 알고리즘 개발
한영복(Young-Bok Han),김성호(Sung-Ho Kim),김변곤(Byon-Gon Kim) 한국전자통신학회 2023 한국전자통신학회 논문지 Vol.18 No.3
최근 가스터빈 발전기는 전력계통의 주파수 조절용으로 널리 사용되고 있다. 가스터빈의 입구온도는 기기의 성능과 수명에 관련된 핵심요소이지만 터빈구조 및 운전환경 등의 이유로 입구온도를 직접 측정하지 않고 가스터빈 배기가스 온도 측정값을 이용하여 입구온도의 추정 값을 구해 이를 연소제어에 사용하고 있다. 특히 재열 가스터빈의 입구온도는 안정적 운전관리에 있어서 매우 중요하지만 제작사가 산출 식에 대한 정보를 제공하지 않고 있어 현장 실무자들은 많은 어려움을 겪고 있다. 이에 본 연구에서는 폴리트로픽 과정식의 기반 위에 머신러닝 기반의 선형회귀 분석기법을 사용하여 가스터빈의 입구온도를 추정할 수 있는 방법을 제시하고자 한다. 또한 선형회귀분석을 통해 얻어진 입구온도 산출 모델식의 유용성 분석과 검증을 통해 입구온도 산출 알고리즘을 제안함으로서 재열 가스터빈 연소튜닝 기술수준 향상에 도움이 되고자 한다. Recently, gas turbine generators are widely used for frequency control of power systems. Although the inlet temperature of a gas turbine is a key factor related to the performance and lifespan of the device, the inlet temperature is not measured directly for reasons such as the turbine structure and operating environment. In particular, the inlet temperature of the reheating gas turbine is very important for stable operation management, but field workers are experiencing a lot of difficulties because the manufacturer does not provide information on the calculation formula. Therefore, in this study, we propose a method for estimating the inlet temperature of a gas turbine using a machine learning-based linear regression analysis method based on a polytropic process equation. In addition, by proposing an inlet temperature calculation algorithm through the usefulness analysis and verification of the inlet temperature calculation model obtained through linear regression analysis, it is intended to help to improve the level of reheat gas turbine combustion tuning technology.
심층신경망 기법을 이용한 재열 가스터빈 입구온도 예측모델에 관한 연구
한영복(Young-Bok Han),김성호(Sung-Ho Kim),김변곤(Byon-Gon Kim) 한국전자통신학회 2023 한국전자통신학회 논문지 Vol.18 No.5
국내 전력계통의 주파수 조정용 발전기로 사용되고 있는 가스터빈은 탄소중립 정책과 더불어 신속한 기동· 정지 및 높은 열효율 등으로 인해 이용률이 증가하고 있다. 가스터빈은 고온의 화염을 이용하여 터빈을 회전시키기 때문에 터빈 입구온도가 기기의 성능과 수명을 좌우하는 핵심요소로 작용하고 있다. 하지만 입구온도는 직접적인 측정이 불가능함에 따라 제작사가 산출한 온도를 이용하거나, 현장 경험을 토대로 하여 예측된 온도를 적용하고 있어서 가스터빈의 안정적인 운전 및 유지관리에 많은 어려움을 겪고 있다. 이에 본 연구에서는 인공신경망에서 많이 사용되고 있는 DNN(: Deep Neural Network) 기반으로 하는 재열 가스터빈의 입구온도를 예측할 수 있는 모델을 제시하고 실측 데이터를 기반으로 제안된 DNN의 성능을 검증하고자 한다. Gas turbines, which are used as generators for frequency regulation of the domestic power system, are increasing in use due to the carbon-neutral policy, quick startup and shutdown, and high thermal efficiency. Since the gas turbine rotates the turbine using high-temperature flame, the turbine inlet temperature is acting as a key factor determining the performance and lifespan of the device. However, since the inlet temperature cannot be directly measured, the temperature calculated by the manufacturer is used or the temperature predicted based on field experience is applied, which makes it difficult to operate and maintain the gas turbine in a stable manner. In this study, we present a model that can predict the inlet temperature of a reheat gas turbine based on Deep Neural Network (DNN), which is widely used in artificial neural networks, and verify the performance of the proposed DNN based on actual data.
솔잎, Pinus densiflora Sieb.et Zucc., 의 항암효과(抗癌效果)에 대한 연구(硏究)
문정조,한영복,김진석,Mooon, Jeong-jo,Han, Young-bok,Kim, Jin-suk 대한수의학회 1993 大韓獸醫學會誌 Vol.33 No.4
The pine needles, Pinus densiflow Sieb. et Zucc., which is a feed for goats showing a low incidence rate of cancer were evaluated to confirm the potent anticancer effects, with or without several conventional anticancer drugs. The pine needles collected from Mt. Buk-Han located near Seoul were extracted with 95% methanol and methand and concentrated. From the methanol extract, SOM-A, was extracted dichlormethane and SOM-B was extracted with ethyl acetate. SOM-C was extracted with distilled water. These extracts were tested for their antitumor activities in vitro and in vivo. Among them, SOM-A and SOM-C exhibited potent antitumor activities described as belows. 1. The cytotoxic effects of SOM-A and SOM-C were examined against in vitro cultured murine and humman tumor cells. SOM-A showed strong cytotoxicity against human tumor cell lines and SOM-C showed strong cytotoxicity against murine tumor cell lines tested. 2. The antitumor effects of SOM-A and SOM-C were examined against P388 and L1210 of mouse ascitic tumors. The highest mean survival time(MST) ration was 151%(P388) for SOM-C(90mg/kg). 3. To compare the antitumor effects of SOM-A, SOM-B, and SOM-C against solid tumors, S-180 and Ehrlich carcinoma were implanted subcutaneously to mice on Day O. The drugs were given intraperitoneally to mice once a day on Days 1-20, and the tumor weights were measured on Day 21. SOM-A showed inhibition of tumor growth more than 50% in the experiment on S-180 and Ehrlich, and SOM-C also markedly inhibited tumor growth. However, SOM-B had no effect. 4. SOM-C combined with ${\alpha}$-interferon and SOM-C combined with Mitomycin-C enhanced the antitumor activities against murine ascitic tumors P388 leukemia.
파두와 황련의 수용성 혼합물(CP2)부터 분리된 항암성분의 구조확인 및 세포독성에 대한 연구
김정한(Jung Han Kim),이상준(Sang Jun Lee),한영복(Young Bok Han),김종배(Jong Bae Kim) 대한약학회 1994 약학회지 Vol.38 No.1
Active fraction, P2, was isolated from natural anti-cancer drug, CP2, by HPLC. We confirmed that P2, includes most of the Isoguanosine and minor components, Berberine and other protoberberine alkaloids, by 1H-NMR and 13C-NMR and measured the cytotoxicity of P2, against various tumor cell-lines. P2, was very effective to all tumor cell-lines, especially to human colon cancer SNU-C2A(ED50; 24mcg) and liver cancer HEP-3B(ED50; 27mcg).
Isoguanosine과 Berberine 1 : 1 혼합물의 항암효과
김정한,이상준,한영복,문정조,김종배,Kim, Jung-Han,Lee, Sang-Jun,Han, Young-Bok,Moon, Jung-Jo,Kim, Jong-Bae 대한약학회 1994 약학회지 Vol.38 No.2
Isoguanosine and berberine 1:1 mixture[l:[1(mole:mole)] has been prepared and evaluated by measuring antitumor effects against various tumor cell lines in culture and in mice. We reported that the synergistic effect of isoguanosine and berberine mixture has been revealed compared with each of isoguanosine and berberine increased by $3{\sim}8$ times than that of each components in various tumor cell lines in vitro. The most effective dose of isoguanosine and berberine mixture was 60 mg/kg/day in mice bearing S-180 solid tumor, the %(1-T/C) values were 70%. Against the P-388 leukemia, isoguanosine-berberine mixture was the most effective at the dose of 60 mg/kg/day, the %T/C values were 163%.