• 한국생산제조학회지
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• 제20권1호
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• pp.53-59
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• 2011

End milling is available for machining the various shape of products and has been widely applied in many manufacturing industries. The quality of products depends on a machine tool performance and machining conditions. Recognition characteristics of the cutting condition is becoming a critical requirement for improving the utilization and flexibility of present-day CNC machine tools. The measurement of tool wear would be performed by coordinate-measuring machine(CMM). However, the usage of CMM requires much time and cost. In order to overcome the difficulties, on-line measurement(OLM) system was applied for a tool wear measurement. This study shows a reliable technique for the reduction of machining error components by developing a system using a CCD camera and machine vision to be able to precisely measure the size of tool wear in flat end milling for CNC machining. The CCD camera and machine vision attached to a CNC machine can determine tool wear quickly and easily.

• 한국자동차공학회논문집
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• 제12권3호
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• pp.184-191
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• 2004

In this study, an inspection system for automotive parts using machine vision has been developed and presented. The system is comprised of six analog CCD cameras, frame grabber, and mechanism that loads the automotive parts to the system for the inspection. An Image processing algorithm for detecting eight different types of defects of oil-seals are developed, and the effectiveness of the algorithm is experimentally verified. Inspection process is completed in 1 second with acceptable accuracy. It is envisaged that this inspection system will have a wide application in the automotive part manufacturing industry in the future.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.255-258
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• 1995

Surface profile is an important paramerer to evaluate accuracy of machined worpiece. It is necessary to acquire this data by in-process measurement. Recent researchers have introduced Machine Vision technique to achieve it. But it is difficult to apply it to industry field yet. In this study, in-process measuring system of surface profile is developed using CCD camera. The effect of illuminance according to incident angle is investigated and surface profile from surface tester and illuminance graph are compared experimentally.

• 대한기계학회논문집A
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• 제28권6호
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• pp.867-875
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• 2004

In order to inspect burr geometry and hole quality in micro-drilling processes, a cost-effective method using an image processing and shape from focus (SFF) methods on the machine tool is proposed. A CCD camera with a zoom lens and a novel illumination unit is used in this paper. Since the on-machine vision unit is incorporated with the CNC function of the machine tool, direct measurement and condition monitoring of micro-drilling processes are conducted between drilling processes on the machine tool. Stainless steel and hardened tool steel are used as specimens, as well as twist drills made of carbide are used in experiments. Validity of the developed system is confirmed through experiments.

• 한국산업정보학회논문지
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• 제19권4호
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• pp.41-52
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• 2014

본 논문은 O링의 치수 측정에 있어 고가의 대 중형 머신비전 장비를 대체할 수 있는 소형 머신 비전 검사 장비에 기반한 O링 부품 내 외경 측정 알고리즘을 제안한다. 백라이트 조명하에 하나의 CCD 카메라를 이용하여 측정 평면으로 부터 영상을 획득하는 소형 머신 비전 검사장비에 의해 획득된 영상을 제안한 영상처리 기법 알고리즘을 이용하여 O링의 외경 및 내경치수를 측정한다. 치수 측정의 정확도를 높이기 위해 렌즈계 왜곡 보정과 원근 왜곡 보정을 소프트웨어적 기법으로 보정 하였고 O링 형상을 고려하여 타원정합 모델을 적용하였으며 보다 타원 정합의 신뢰성을 높이기 위해 RANSAC알고리즘을 적용하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.695-698
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• 2000

Round-cornering machines are mainly used for cornering of stiffners for ship buildings. In the present time they have been operated manually by operators. so they are need to be operated automatically without regard to any shapes of stiffners. We developed the automatic round cornering system which consists of CCd Camera, PC and laser diode to detect automatically the edge of stiffners to be processed

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.270-278
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• 2000

A machine vision system using charge coupled device(CCD) camera for the weed detection in a radish farm was developed. Shape features were analyzed with the binary images obtained from color images of radish and weeds. Aspect, Elongation and PTB were selected as significant variables for discriminant models using the STEPDISC option. The selected variables were used in the DISCRIM procedure to compute a discriminant function for classifying images into one of the two classes. Using discriminant analysis, the successful recognition rate was 92% for radish and 98% for weeds. To recognize radish and weeds more effectively than the discriminant analysis, an artificial neural network(ANN) was used. The developed ANN model distinguished the radish from the weeds with 100%. The performance of ANNs was improved to prevent overfitting and to generalize well using a regularization method. The successful recognition rate in the farms was 93.3% for radish and 93.8% for weeds. As a whole, the machine vision system using CCD camera with the artificial neural network was useful to detect weeds in the radish farms.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.494-498
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• 1998

이 논문은 에나멜 전선의 제조공정의 자동화에 있어서 핵심역할을 하는 보빈의 자동인식을 위한 머신 비젼 시스템에 관한 것이다. 이 시스템의 역할은 컨베이어 라인의 팔레트 위에 놓인 보빈들의 영상을 CCD 카메라로 취득, 분석하여 보빈 형태, 색상, 제조공정번호 등의 다양한 정보를 추출하여, 전체 생산공정을 제어하는 주 컴퓨터로 보내는 일을 수행한다. 이 비젼 시스템은 개발된 후 에나멜 전선 생산공장에 설치되어 일정 시험기간을 거쳐 현재 성공적으로 운영되고 있다.

• 대한기계학회논문집A
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• 제31권10호
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• pp.993-998
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• 2007

To verify the 2D or 3D positioning accuracy of a multi-axes stage is not easy, particularly, in the case the moving path of the stage is not linear. This paper is a study on a measuring method for the curved path accurately. A machine vision technique is used to trace the moving path of two-axes stage. To improve the accuracy of machine vision, a zoom lens is used for the 2D micro moving path. The accuracy of this method depends of the CCD resolution and array align accuracy with the zoom lens system. Also, a further study for software algorithm is required to increase the tracing speed. This technique will be useful to trace a small object in the 2D micro path in real-time accurately.

• Journal of Biosystems Engineering
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• 제25권1호
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• pp.55-62
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• 2000

Autonomous farm operation needs to be developed for safety, labor shortage problem, health etc. In this research, an autonomous tractor for tillage was investigated using machine vision and a fuzzy logic controller(FLC). Tractor heading and offset were determined by image processing and a geomagnetic sensor. The FLC took the tractor heading and offset as inputs and generated the steering angle for tractor guidance as output. A color CCD camera was used fro the image processing . The heading and offset were obtained using Hough transform of the G-value color images. 15 fuzzy rules were used for inferencing the tractor steering angle. The tractor was tested in the file and it was proved that the tillage operation could be done autonomously within 20 cm deviation with the machine vision and the FLC.