• 한국산학기술학회논문지
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• 제16권4호
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• pp.2609-2619
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• 2015

본 연구는 노인요양시설 노인들의 우울과 건강상태, 일상생활수행능력, 수면상태의 관련성을 파악하고자 실시하였다. 연구대상자는 노인요양시설에서 거주하는 만 65세 이상의 노인을 대상으로 하였다. 노인요양시설 노인들의 우울 관련성은 시력상태, 치아상태, 수면의 질, 수면상태 등과 관련이 있었으며, 시력상태가 나쁜 군, 치아상태가 나쁜 군, 수면의 질이 나쁜 군, 수면장애가 있는 군에서 높게 나타났다. 우울과의 상관관계에서는 우울과 연령과는 음의 상관관계로 나타났고, 치아상태, 수면의 질 등이 양의 상관관계가 있는 것으로 나타났다. 노인요양시설 노인들의 우울에 영향을 미치는 요인으로 시력상태, 치아상태, 수면상태, 청력상태 등이 관련성이 높게 나타났다. 결론적으로, 노인요양시설 노인들의 우울과의 관련성은 개인이 인지하는 건강상태와 관련이 높으며, 건강관리와 간호중재도 개인별 건강상태에 세심한 관심과 시력상태, 치아상태가 낮은 노인관리가 중요하다고 하겠다.

• 한국산업정보학회논문지
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• 제16권2호
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• pp.65-72
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• 2011

본 논문에서는 단일 카메라로부터 주어진 영상을 실시간으로 장애물과 비장애물 영역으로 분류 한 후 VFH를 이용하여 안전한 경로를 선정하는 실시간 주행 시스템을 개발한다. 제안된 시스템은 배경 분류기, 점유 그리드맵 생성기와 VFH기반의 선정기로 구성된다. 배경 분류기는 입력된 $320{\times}240$ 영상의 색조와 명도 정보를 이용하여 실시간으로 배경파 장애물 영역을 분류한다. 점유 그리드맵 생성기는 이를 바탕으로 위험도에 따라 10개의 그레이 레벨을 가지는 $32{\times}24$의 점유 그리드맵을 생성한다. VFH를 이용하여 폴라 히스토그램을 작성한 후 밀도가 낮은 곳으로 주행 경로를 결정 한다. 제안된 기술의 효율성을 증명하기 위하여 다양한 형태의 장애물을 포함하는 실내 및 실외 환경에서 평가하였으며 센서 기반의 그 결과는 기존의 센서기반의 주행시스템과 비교 되었다. 그 결과 제안된 시스템은 88%의 정확도를 보였으며, 기존의 시스템보다 실시간으로 빠르고 안전한 주행을 수행할 수 있음이 증명되었다.

• 한국정밀공학회지
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• 제17권12호
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• pp.54-60
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• 2000

Research about tool condition monitoring has been done until now for product automation and unmaned system. But it is hard to apply it to the industrial field due to its cost and reliability. This paper presents the new method of tool wear measurement using Marpos gauge. This is a kind of touch sensor, so its cost is lower than vision system. And it is not affected by dust and illumination, which are important in vision system. This proposed method use tool clearance angle to measure flank wear. Experimental results compared with vision system shows that this method is available for tool condition monitoring system.

• 한국정밀공학회지
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• 제16권2호통권95호
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• pp.176-182
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• 1999

This paper presents a new autonomous kinematic calibration technique by using a laser-vision sensor called "Perceptron TriCam Contour". Because the sensor measures by capturing the image of a projected laser line on the surface of the object, we set up a long, straight line of a very fine string inside the robot workspace, and then allow the sensor mounted on a robot to measure the point intersection of the line of string and the projected laser line. The point data collected by changing robot configuration and sensor measuring are constrained to on a single straght line such that the closed-loop calibration method can be applied. The obtained calibration method is simple and accurate and also suitable for on-site calibration in an industrial environment. The method is implemented using Hyundai VORG-35 for its effectiveness.

• 제어로봇시스템학회논문지
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• 제19권12호
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• pp.1072-1080
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• 2013

In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 학술대회 논문집 전문대학교육위원
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• pp.41-45
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• 2002

In industrial computer vision systems, the image quality is dependent on the parameters such as light source, illumination method, optics, and surface properties. Most of them are related with the lighting system, which is designed in heuristic, based on the designer's experimental knowledge, In this paper, a design code by which the optimal lighting method and light source for computer vision systems can be found are suggested based on experimental results, To prove the usefulness of the design code, it is applied to the lighting system design of the transistor marking inspection system and the results are presented.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.294-303
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• 2021

Various types of sensors are used at industrial sites to measure vibration. With the increase in the diversity of vibration measurement methods, vibration monitoring methods using camera equipment have recently been introduced. However, owing to the physical limitations of the hardware, the measurement resolution is lower than that of conventional sensors, and real-time processing is difficult because of extensive image processing. As a result, most such methods in practice only monitor status trends. To address these disadvantages, a high-resolution vibration measurement method using image analysis of the edge region of the structure has been reported. While this method exhibits higher resolution than the existing vibration measurement technique using a camera, it requires significant amount of computation. In this study, a method is proposed for rapidly processing considerable amount of image data acquired from vision equipment, and measuring the vibration of structures with high resolution. The method is then verified through experiments. It was shown that the proposed method can fast measure vibrations of structures remotely.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.504-509
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• 1995

In this paper, we developed a position correction system of industrial robot for door-chassis assembly task. With the aid of a dedicated vision system, industrial robot accomplished visually acceptable door-chassis's assembly task. The alogorithm of the position detection of notch and 2 dimesional position correction algorithm are noteworthy. The obtained algorithms were satisfatorily implemented for a real door-chassis model.

• 산업경영시스템학회지
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• 제47권1호
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• pp.9-19
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• 2024

Deep learning-based computer vision anomaly detection algorithms are widely utilized in various fields. Especially in the manufacturing industry, the difficulty in collecting abnormal data compared to normal data, and the challenge of defining all potential abnormalities in advance, have led to an increasing demand for unsupervised learning methods that rely on normal data. In this study, we conducted a comparative analysis of deep learning-based unsupervised learning algorithms that define and detect abnormalities that can occur when transparent contact lenses are immersed in liquid solution. We validated and applied the unsupervised learning algorithms used in this study to the existing anomaly detection benchmark dataset, MvTecAD. The existing anomaly detection benchmark dataset primarily consists of solid objects, whereas in our study, we compared unsupervised learning-based algorithms in experiments judging the shape and presence of lenses submerged in liquid. Among the algorithms analyzed, EfficientAD showed an AUROC and F1-score of 0.97 in image-level tests. However, the F1-score decreased to 0.18 in pixel-level tests, making it challenging to determine the locations where abnormalities occurred. Despite this, EfficientAD demonstrated excellent performance in image-level tests classifying normal and abnormal instances, suggesting that with the collection and training of large-scale data in real industrial settings, it is expected to exhibit even better performance.

• 한국전자통신학회논문지
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• 제8권1호
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• pp.159-164
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• 2013

최근 자동화 시스템에 있어 중요한 요소인 비전과 모션 컨트롤러를 통합한 솔루션이 많이 개발되고 있다. 다만 이러한 솔루션은 비전 처리와 모션 컨트롤을 네트워크로 통합하거나 하나의 모듈에 투 칩 솔루션으로 구성된 경우가 많다. 본 연구에서는 최근에 개발된 확장형 프로세싱 플랫폼인 Zynq-7000을 이용한 비전 및 모션 제어기를 통합한 원 칩 솔루션을 구현하였다. 또한 모션 컨트롤은 제어의 실시간이 보장되면서 대량의 데이터를 처리할 수 있는 개방형 표준 이더넷 호환성을 가지고 있는 산업용 이더넷 프로토콜인 EtherCAT을 적용하였다.