• Title/Summary/Keyword: 구형 캡

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Free Vibration Analysis of a Circular Cylindrical Shell with a Spherical Cap (구형 캡이 결합된 외팔 원통 쉘의 고유진동 해석)

  • J.S. Yim;D.S. Sohn
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11a
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    • pp.355.2-355
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    • 2002
  • The receptance method was applied for the analysis of a cylindrical shell with a spherical cap attached at an arbitrary axial position of the shell. The boundary condition of the shell considered here was clamped-free condition. Before the analysis of the shell/spherical cap combined structure, natural frequencies of the cap and the shell were calculated separately and then they were used in the calculation of the frequencies of the combined structure by the receptance method. (omitted)

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Free Vibration Analysis of a Curvatured Plate Welded to a Clamped-Free Circular Cylindrical Shell (곡률 원판이 결합된 외팔 원통 쉘의 고유진동 해석)

  • Yim, J.S.;Sohn, D.S.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11b
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    • pp.529-534
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    • 2002
  • The receptance method was applied for the analysis of a cylindrical shell with a curvaturated plate attached at the top of the shell. The boundary conditions of the shell considered here were clamped at the bottom and free at the top of the shell. Before the analysis of the shell/plate combined structure, the natural frequencies of the plate and the shell were calculated separately and then they were used in the calculation of the frequencies of the combined structure by the receptance method. The frequency equation of the combined structure was derived from the continuity condition at the junction of the shell and the plate. The frequencies for various curvature factors of the plate were presented and compared with those from ANSYS to show its validity of the present method.

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Development of Special Robot Welding Nozzle for the Reduction of CO2 Gas Consumption (CO2 가스 절약형 로봇 용접용 노즐 개발에 관한 연구)

  • Lee, Jongkil
    • 대한공업교육학회지
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    • v.33 no.1
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    • pp.282-296
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    • 2008
  • Present automobile robot welding use $CO_2$ inert gas as a shielding fluid. The inert gas is spreading out and consumable. This present welding mechanism interfered with the welding nozzle. After welding several places have welding defects. Therefore, to reduce the $CO_2$ inert gas and to avoid interference with the material and to increase production modified nozzle which composed of cap and tip are needed. Suggested modified nozzle assembly composed of two stages i.e. $1^{st}$ and $2^{nd}$ stage. At the second stage it has 8 holes which is 3mm of diameter around the circumference. On the base of experimental results the inert $CO_2$ gas discharge reduced to 47% and welding defects decreased also. Modified two stage welding cap can be applied to the present robot welding machine and save the prime cost.

A Reference Frame Selection Method Using RGB Vector and Object Feature Information of Immersive 360° Media (실감형 360도 미디어의 RGB 벡터 및 객체 특징정보를 이용한 대표 프레임 선정 방법)

  • Park, Byeongchan;Yoo, Injae;Lee, Jaechung;Jang, Seyoung;Kim, Seok-Yoon;Kim, Youngmo
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1050-1057
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    • 2020
  • Immersive 360-degree media has a problem of slowing down the video recognition speed when the video is processed by the conventional method using a variety of rendering methods, and the video size becomes larger with higher quality and extra-large volume than the existing video. In addition, in most cases, only one scene is captured by fixing the camera in a specific place due to the characteristics of the immersive 360-degree media, it is not necessary to extract feature information from all scenes. In this paper, we propose a reference frame selection method for immersive 360-degree media and describe its application process to copyright protection technology. In the proposed method, three pre-processing processes such as frame extraction of immersive 360 media, frame downsizing, and spherical form rendering are performed. In the rendering process, the video is divided into 16 frames and captured. In the central part where there is much object information, an object is extracted using an RGB vector per pixel and deep learning, and a reference frame is selected using object feature information.