• The Journal of the Acoustical Society of Korea
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• v.17 no.7
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• pp.91-100
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• 1998

본 논문에서는 지수함수적 감쇄신호의 매개변수를 효율적으로 추정하기 위한 신호 모델링 기법을 제안한다. 이 방법은 맥놀이 주파수 성분을 갖으면서 과도기 형태 신호인 성 덕대왕 신종의 음파(공중음파 및 지중음파)를 분석하기 위하여 개발되었으며 선형예측모델 을 기본으로 하고 있다. 제안된 방법은 일반적인 데이터 행렬 대신에 자기상관 유사행렬을 사용하였으며 SVD 방법을 이용하여 매개변수를 추정한다. 성덕대왕 신종의 스펙트럼 및 감 쇄계수 특성을 분석하기 위하여 제안된 방법을 수집한 데이터에 적용하였고 분석결과를 토 대로하여 고유주파수 신호의 감쇄계수 및 움통의 역할도 규명하였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.37-42
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• 1983

The TV IF SAW filter if designed using the windowing method. The procedure for fabricating SAW filters is described. The filter is fabricated on the Y-cut, Z-propagation LiNbO3 wafer. The passband ripple and the smaller upper sidelobe attenuation are obseryed. Further improvements and the mass production can be expected.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.4
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• pp.130-140
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• 2017

Lightning protective design of an aircraft fuel system is closely related to the safety of the flight. Recently, composite material in building an aircraft becomes more important because it can reduce the weight of the aircraft. The composite materials decrease the protection against the effect of lightning. Lightning protective design of metal material aircraft has been researched for a long time and the design technique has been announced widely. However, research on the lightning protective design using composite material aircraft is very limited. In this study, lightning protective design for fuel tank structural component, access cover, fuel filler cap and drain valve in carbon fiber composite material aircraft have been presented. To show the compliance with FAA airworthiness standard regarding the presented protection designs, three steps, including lightning strike analysis, lightning environment analysis and certification test, were conducted in accordance with FAA AC 20-53.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.305-312
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• 2023

Physics-Informed Neural Network (PINN) is used to invert bubble size distributions from attenuation losses. By considering a linear system for the bubble population inversion, Adaptive Learned Iterative Shrinkage Thresholding Algorithm (Ada-LISTA), which has been solved linear systems in image processing, is used as a neural network architecture in PINN. Furthermore, a regularization based on the linear system is added to a loss function of PINN and it makes a PINN have better generalization by a solution satisfying the bubble physics. To evaluate an uncertainty of bubble estimation, deep ensemble is adopted. 20 Ada-LISTAs with different initial values are trained using the same training dataset. During test with attenuation losses different from those in the training dataset, the bubble size distribution and corresponding uncertainty are indicated by average and variance of 20 estimations, respectively. Deep ensemble Ada-LISTA demonstrate superior performance in inverting bubble size distributions than the conventional convex optimization solver of CVX.