• Title/Summary/Keyword: 크레이터

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A Deep-Learning Based Automatic Detection of Craters on Lunar Surface for Lunar Construction (달기지 건설을 위한 딥러닝 기반 달표면 크레이터 자동 탐지)

  • Shin, Hyu Soung;Hong, Sung Chul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.6
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    • pp.859-865
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    • 2018
  • A construction of infrastructures and base station on the moon could be undertaken by linking with the regions where construction materials and energy could be supplied on site. It is necessary to detect craters on the lunar surface and gather their topological information in advance, which forms permanent shaded regions (PSR) in which rich ice deposits might be available. In this study, an effective method for automatic detection of lunar craters on the moon surface is taken into consideration by employing a latest version of deep-learning algorithm. A training of a deep-learning algorithm is performed by involving the still images of 90000 taken from the LRO orbiter on operation by NASA and the label data involving position and size of partly craters shown in each image. the Faster RCNN algorithm, which is a latest version of deep-learning algorithms, is applied for a deep-learning training. The trained deep-learning code was used for automatic detection of craters which had not been trained. As results, it is shown that a lot of erroneous information for crater's positions and sizes labelled by NASA has been automatically revised and many other craters not labelled has been detected. Therefore, it could be possible to automatically produce regional maps of crater density and topological information on the moon which could be changed through time and should be highly valuable in engineering consideration for lunar construction.

An Analysis of Undergraduate Students' Mental Models on the Mechanism of the Moon Craters Formation (달 크레이터 생성에 대한 대학생들의 정신모형 분석)

  • Lee, Ho;Cho, Hyun-Jun;Lee, Hyo-Nyong
    • Journal of the Korean earth science society
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    • v.28 no.6
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    • pp.655-672
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    • 2007
  • The purpose of this study was to investigate information sources and types of reasoning that non-astronomy major undergraduate students used to build their mental models on the mechanism of the Moon craters formation. In-depth interview was used to collect qualitative data, and the questions for the interview were developed through an analytical induction method. We interviewed four students individually by using Seidman's interview step. The findings revealed that the participants built nonscientific mental models, and yet they held a consistent explanatory framework. The students explained that the crater was made by the fall of a meteorite. They all suggested a similar shape of meteorite even though their drawings about the shape of craters and its related to variables were different from one another. The information sources that the participants used fur their explanatory frameworks were varied, i.e., daily experiences, subject knowledges, and intuition. In addition, they used causal reasoning, intuitional reasoning, knowledge based reasoning, and analogical reasoning.

Crater Wear Volume Calculation and Analysis (크레이터 마모의 체적계산 및 분석법)

  • Jeong, Jin-Seok;Cho, Hee-Geun;Yoon, Moon-Chul
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.18 no.3
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    • pp.248-254
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    • 2009
  • The worn crater wear geometry of coated tools after machining has been configured by using Confocal Laser Scanning Microscopy(CLSM) and the Wavelet-based filtering technique. The CLSM can be well suited to construct the three-dimensional crater wear on the rake surfaces of coated tips. However, The raw heightness data of HEI(height encoded image) acquired by CLSM must be filtered due to the electronic and imaging noise occurring in constructing the crater image. So the Wavelet-based filtering algorithm is necessary to denoise the shape features in a micro scales so as to realize accurate crater wear topography analysis. The crater wear patterns filtered enable us to predict the crater wear shape in order to study the tool wear evolution. The study shows that the technique by combining the CLSM and Wavelet-based filtering is an excellent one to obtain the geometries of worn tool rake surfaces over a wide range of surface resolution in a micro scale.

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유한요소법을 이용한 단발 방전의 시뮬레이션

  • 김동길;민병권;이상조
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.05a
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    • pp.253-253
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    • 2004
  • 방전가공은 현재의 정밀 금형산업에서는 필수적인 가공방법이나, 공작물과 전극사이에서 방전이 발생할 때 고온고압의 플라즈마 상태에서 재료를 제거하는 메카니즘에 대한 해석은 아직도 많은 연구 대상이다. 방전가공은 기본적으로 3단계의 과정으로 구별할 수 있는데, 첫째 공작물과 전극의 간격과 기하학적 형상, 전압에 의해서 전계가 집중되어 절연체의 절연강도보다 초과하면 절연체가 이온화되어 방전이 시작된다. 둘째, 전극과 공작물이 통전이 되어 플라즈마 채널이 형성되면서 열에너지에 의하여 공작물이 용융 증발이 발생한다.(중략)

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Lunar Crater Detection using Deep-Learning (딥러닝을 이용한 달 크레이터 탐지)

  • Seo, Haingja;Kim, Dongyoung;Park, Sang-Min;Choi, Myungjin
    • Journal of Space Technology and Applications
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    • v.1 no.1
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    • pp.49-63
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    • 2021
  • The exploration of the solar system is carried out through various payloads, and accordingly, many research results are emerging. We tried to apply deep-learning as a method of studying the bodies of solar system. Unlike Earth observation satellite data, the data of solar system differ greatly from celestial bodies to probes and to payloads of each probe. Therefore, it may be difficult to apply it to various data with the deep-learning model, but we expect that it will be able to reduce human errors or compensate for missing parts. We have implemented a model that detects craters on the lunar surface. A model was created using the Lunar Reconnaissance Orbiter Camera (LROC) image and the provided shapefile as input values, and applied to the lunar surface image. Although the result was not satisfactory, it will be applied to the image of the permanently shadow regions of the Moon, which is finally acquired by ShadowCam through image pre-processing and model modification. In addition, by attempting to apply it to Ceres and Mercury, which have similar the lunar surface, it is intended to suggest that deep-learning is another method for the study of the solar system.

국산초경공구의 절삭성에 관한 비교 연구

  • 김용성外
    • Journal of the KSME
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    • v.20 no.6
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    • pp.474-488
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    • 1980
  • 이제까지의 결과를 종합하여 보면 다음과 같은 결론을 얻을 수 있다. 1. 국산 비피막공구는 의 산에 비하여 많은 절삭영역에서 양호한 성능을 가지고 있다. 2. 국산 비피막공구 W2는 중간 절 삭 영역에서 국산 W1과 외산 W3, W4보다 우수한 성능을 나타낸다. 3. W1은 저속이거나 절삭 깊이가 클 때, W2보다 좋은 성능을 가진다. 4. W1은 대체로 플랭크 마모에 의하여, W2는 저속. 저이송에서는 프랭크마모 그리고 그밖의 영역에서는 크레이터 마모에 의하여 수명이 결정된다. 5. 국산 피막공구 CW7은 외산 CW10, 13에 비하여 내마모성이 매우 좋다. 6. 중간절삭영역에서 W 2의 표면조도는 W1, W3, W4에 비하여 훨씬 좋다. 7. 피막층 유무와 피막재질에 따른 국산 및 외산의 절삭력 차이는 거의 없다.

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A Study on the Development of Measurement Setup for Crater Wear by Diffraction Grating in Turning (선삭에서 회절격자를 이용한 크레이터마모 측정장치 개발에 관한 연구)

  • Kim, Yeong-Il;Kim, Se-Jin
    • Journal of the Korean Society for Precision Engineering
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    • v.9 no.1
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    • pp.82-95
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    • 1992
  • There is the high interest for sensing of tool wear with the aim of controlling machine tools productivity from the point of view of qualitity. Difficulties in this measurement are also known. This study is on the development of measurement setup for crater wear by CCD image inturning. In this study, the crater wear measurement system consists of the He-Ne gas laser, diffraction grating. CCD camera, noise filter, slit, microcomputer, diverging lens, converging lens and so on. He-Ne laser beam passes through a diverging lens and a diffraction grating is positioned properly. A converging lens focuses so that the interference fringes can be obtained on the crater wear. Performance test revealed that the developed image technique provides precise, absolute tool-wear quantification and reduces human measurement errors. The results obtained are as follows 1. The digitizing of one image requires less than 2ses. 2. It can give detailed information on crater wear with limited times and errors 3. All parameters required by specification are easily obtained for several points of the cutting edge.

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Characteristics of tool wear and cutting temperature in machining of SUS 304 (SUS 304 절삭시 공구마모와 절삭온도의 특성)

  • Kwon, Y.K.
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.1
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    • pp.71-79
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    • 1994
  • The aim of this study is to analyze the behavier of SUS 304 during the cutting process and the resulting cutting temperaturce. Since SUS 304 is a difficult-to-machine material, tool damage is largely affected by the suitability of cutting conditions. Therefore, in varying such cutting conditions, the experiment investigates the relations between cutting temperature and tool wear during the cutting process. All the cutting temperature data were manipulated successfully, and the tool temperature distributions were analyzed by a finite element method based on the acquisition data. In the results, the characteristics of cutting temperature are related to the difficulty of machining characteristics.

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The Wear Behavior and Cutting Characteristics of Coated Tools (코팅공구의 마모 및 절삭특성)

  • 정진혁;윤형석;최덕기;주종남
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.3-8
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    • 1996
  • To enhance the cutting performance of the tool, single or multilayer coating is applied on the substrate of the tool. Coating material reduces cutting force and heat generation in tool-chip contact zone and enhances resistance against abrasive wear. This paper presents that the effect of different coatings on abrasive wear resistance varies with work material and the flank wear rate is different with depth of cut. Crater wear rate is also found to decrease with higher thermal diffusivity of coating material. It is verified that the estimated thermal diffusivity of multilayer coating has consistent effect on the crater wear.

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