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Seongpil Jeong(Seongpil Jeong),Hye-Won Kim(Hye-Won Kim),Kyungjin Cho(Kyungjin Cho),Dongjin Yang(Dongjin Yang),Seong-Rae Kim(Seong-Rae Kim),Soon-Ho Park(Soon-Ho Park) 적정기술학회 2022 적정기술학회지(Journal of Appropriate Technology) Vol.8 No.2
Recently, the unbalanced water demand and supply have been occurred globally due to the climate change, industrialization, and population increase. The water shortage problem became much severe in the developing countries because the low-stage of infrastructure might result in frequent limitation of water and transportation of water. Therefore, sustainable water supplying option is the key for the boosting the local economy. The Mekong Delta area produce most of the products in agriculture and fishery in Vietnam. However, due to low income and vast area, the infrastructure for water supply has been limited in the Mekong Delta area. Moreover, due to reduced Mekong-river flow by the dam construction in upper reaches, increased seawater level by the global warming, and increased unexpected drought and flooding by the climate change, the water supply in the Mekong delta is becoming hard. Therefore, sustainable water supplying option was required. In this study, the reverse osmosis-based desalination process could use undrinkable saline water as the feed water coupled with photovoltaic panel was suggested. In order to install the decentralized and off-grid type water production plant in the proper place in the Mekong Delta, the KIST, VKIST, and central and local governments in Vietnam collaborated. The RO plant could be successfully installed by the help of the partners and the operational conditions have been monitored. If the water providing option could be separated according to the purposes such as drinking usage and other water usage, the more technical options could be applied for the water production.
Seongpil Cho,Jongseo Park,Minjoo Choi 한국해양공학회 2021 韓國海洋工學會誌 Vol.35 No.4
This paper describes a recurrent neural network (RNN) for the fault classification of a blade pitch system of a spar-type floating wind turbine. An artificial neural network (ANN) can effectively recognize multiple faults of a system and build a training model with training data for decision-making. The ANN comprises an encoder and a decoder. The encoder uses a gated recurrent unit, which is a recurrent neural network, for dimensionality reduction of the input data. The decoder uses a multilayer perceptron (MLP) for diagnosis decision-making. To create data, we use a wind turbine simulator that enables fully coupled nonlinear time-domain numerical simulations of offshore wind turbines considering six fault types including biases and fixed outputs in pitch sensors and excessive friction, slit lock, incorrect voltage, and short circuits in actuators. The input data are time-series data collected by two sensors and two control inputs under the condition that of one fault of the six types occurs. A gated recurrent unit (GRU) that is one of the RNNs classifies the suggested faults of the blade pitch system. The performance of fault classification based on the gate recurrent unit is evaluated by a test procedure, and the results indicate that the proposed scheme works effectively. The proposed ANN shows a 1.4% improvement in its performance compared to an MLP-based approach.
LSTM-Autoencoder를 이용한 부유식 풍력터빈 블레이드 피치 시스템의 이상징후 감지
조성필(Seongpil Cho) 항공우주시스템공학회 2024 항공우주시스템공학회지 Vol.18 No.4
본 논문은 부유식 풍력터빈의 블레이드 피치 시스템에서 발생하는 이상을 조기에 감지하기 위한 LSTM-Autoencoder 모델 기반의 이상징후 감지 시스템을 설명한다. 발전소 모니터링 시스템에 활용되는 센서 데이터는 주로 시계열 데이터로 구성되며, LSTM 네트워크는 이러한 시계열 데이터를 분석하기 위해 두 개의 단방향 LSTM 네트워크로 구성된다. 이를 통해 순차 데이터에 숨겨진 장기 의존성을 효과적으로 발견할 수 있다. 한편, 오토인코더 메커니즘은 정상상태 데이터로부터만 학습하여 이상상태를 분류될 수 있기 때문에 이 두 가지 네트워크를 결합하여 시스템에 발생하는 이상징후를 효과적으로 감지할 수 있다. 제안된 프레임워크의 효과를 입증하기 위해 풍력 터빈 모델에서 수집한 실제 다변량 시계열 데이터셋을 적용하였다. LSTM-AE 모델은 높은 이상징후 감지 정확도를 달성하여 우수한 성능을 보였다. This paper presents an anomaly detection system that uses an LSTM-Autoencoder model to identify early-stage anomalies in the blade pitch system of floating wind turbines. The sensor data used in power plant monitoring systems is primarily composed of multivariate time-series data for each component. Comprising two unidirectional LSTM networks, the system skillfully uncovers long-term dependencies hidden within sequential time-series data. The autoencoder mechanism, learning solely from normal state data, effectively classifies abnormal states. Thus, by integrating these two networks, the system can proficiently detect anomalies. To confirm the effectiveness of the proposed framework, a real multivariate time-series dataset collected from a wind turbine model was employed. The LSTM-autoencoder model showed robust performance, achieving high classification accuracy.
A Study on Official Development Assistance (ODA) in Science and Technology in Korea
Seongpil Jeong(정성필),Ik Hyun Cho(조익현),Dockko Seok(독고석),Yong-soo Kim(김용수),Ji-hyun Moon(문지현),Jeyong Yoon(윤제용) 적정기술학회 2018 적정기술학회지(Journal of Appropriate Technology) Vol.4 No.2
한국의 원조를 받던 나라에서 원조하는 나라로 변화한 유일한 나라로서, 경제협력개발기구(OECD) 가입과 함께 다양한 ODA 사업을 추진해오고 있다. 한국은 2010년까지 GNI 대비 0.2%의 예산을 ODA에 배분하는 것을 목표로, ODA 사업에 대한 예산을 지속적으로 증액하고 있다. ODA 사업의 확대는 각 부처의 ODA 사업 확대에도 기여를 하고 있는데, 원조의 효과성 제고를 위하여 과학기술 분야 ODA 확대의 중요성이 부각되어 왔으며, 그 중 한 분야로서 수원국의 여건에 부합하는 과학기술로서 ‘적정기술’로 불리는 사업분야의 관심이 증대되고 있다. 이 논문은 1999년부터 현재까지, 과학기술 ODA의 연차별, 연구 내용별 및 부처별 현황을 분석하여 수록함으로써, 과학기술 ODA 분야에 관심있는 독자들에게 정보를 제공하고자 한다. Korea is the only country which had been helped from developed countries and is now helping developing countries. Various ODA programs have been actively conducted by Korea after joining the OECD in 1999. Recently, Korea increases the ODA funds to achieve the goal of ODA/GNI ratio 0.2% until 2020. Science and technology ODA (so called appropriate technology) is a huge issue because the departments or agencies of Korean government also increase ODA funds. This research will provide the information of Korean science and technology ODA according to the research areas and funding sources since 1999.
형상기억합금 트러스 구조물을 이용한 스텐트의 설계 및 해석
양성필(Seongpil Yang),김상헌(Sanghaun Kim),조맹효(Manghyo Cho) 대한기계학회 2008 대한기계학회 춘추학술대회 Vol.2008 No.11
Recently, many patients related to heart disease have surgical operation by expanding a blood vessel to treat the angiostenosis. So far most angioplasties have been performed using balloon-dilative stent made of stainless steel. Some researchers are studying the stent made of shape memory alloy (SMA) to operate the angioplasty more easily. and there are several papers which introduce the angioplasty using SMA. However, most of the analysis models for stents are constructed using solid elements. So much computing time is required to solve the analysis model. In this study, we suggest the SMA stent model using 1D truss element which is much faster than stent model using 3D solid element. To represent non-linear behavior of SMA, we apply 1D SMA constitutive equation of Lagoudas’. Pseudo-elastic behavior of stent structures is presented as a numerical example.