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초음속 엔진 모델 연소기에서의 연소불안정 및 제어 시험 기법
최호진(Hojin Choi),황용석(Yongseok Hwang),진유인(Youin Jin),박익수(Iksoo Park),윤현걸(Hyungull Yoon),강상훈(Sanghun Kang),이양지(Yangji Lee) 한국추진공학회 2009 한국추진공학회 학술대회논문집 Vol.2009 No.5
초음속 엔진으로부터 구성한 모델 연소기를 설계/제작하여 연소시험 중 발생하는 연소불안정을 측정하고 화염안정화 장치를 이용하여 2차 연료를 분사하는 방법으로 연소불안정을 능동제어하는 기법에 관해 연구하였다. 연소실 압력측정이나 화염의 광학적 계측을 통해 연소불안정 주파수를 검출하였고, 고속으로 운용할 수 있는 마그네틱 밸브를 구동기로 선정하여 밸브 후단 압력 및 2차 분사되는 연료의 분무의 광학적 계측을 통해 연료 변조 특성을 확인하였다. The method of test for observing the combustion instability and controling the instability actively by using secondary injection of fuel through flame stabilizer was studied by constructing model combustor of supersonic engine. The frequency of combustion instability was detected by measuring the pressure of combustor using pressure sensor and by optical sensing of flame intensity. Electro-magnetic valve was adopted as actuator for active control and the characteristics of modulated fuel was studied by measured pressure of valve outlet and scattering signal of spray at secondary fuel injection.
An Improved Multi-resolution image fusion framework using image enhancement technique
Hojin Jhee(지호진),Chulhee Jang(장철희),Sanghun Jin(진상훈),Yonghee Hong(홍용희) 한국컴퓨터정보학회 2017 韓國컴퓨터情報學會論文誌 Vol.22 No.12
This paper represents a novel framework for multi-scale image fusion. Multi-scale Kalman Smoothing (MKS) algorithm with quad-tree structure can provide a powerful multi-resolution image fusion scheme by employing Markov property. In general, such approach provides outstanding image fusion performance in terms of accuracy and efficiency, however, quad-tree based method is often limited to be applied in certain applications due to its stair-like covariance structure, resulting in unrealistic blocky artifacts at the fusion result where finest scale data are void or missed. To mitigate this structural artifact, in this paper, a new scheme of multi-scale fusion framework is proposed. By employing Super Resolution (SR) technique on MKS algorithm, fine resolved measurement is generated and blended through the tree structure such that missed detail information at data missing region in fine scale image is properly inferred and the blocky artifact can be successfully suppressed at fusion result. Simulation results show that the proposed method provides significantly improved fusion results in the senses of both Root Mean Square Error (RMSE) performance and visual improvement over conventional MKS algorithm.