• Applied Microscopy
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• 제50권
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• pp.27.1-27.6
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• 2020

Transition metal dichalcogenides (TMD), which is composed of a transition metal atom and chalcogen ion atoms, usually form vacancies based on the knock-on threshold of each atom. In particular, when electron beam is irradiated on a monolayer TMD such as MoS₂ and WS₂, S vacancies are formed preferentially, and they are aligned linearly to constitute line defects. And then, a hole is formed at the point where the successively formed line defects collide, and metal clusters are also formed at the edge of the hole. This study reports a process in which the line defects formed in a monolayer WS₂ sheet expends into holes. Here, the process in which the W cluster, which always occurs at the edge of the formed hole, goes through a uniform intermediate phase is explained based on the line defects and the formation behavior of the hole. Further investigation confirms the atomic structure of the intermediate phase using annular dark field scanning transition electron microscopy (ADF-STEM) and image simulation.

• 한국정밀공학회지
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• 제33권6호
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• pp.459-467
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• 2016

Using a line scan camera and a Galvano mirror, we constructed a high-speed line-scanning microscope that can generate 2D images ($8000{\times}8000pixels$) without any moving parts. The line scanner consists of a Galvano mirror and a cylindrical lens, which creates a line focus that sweeps over the sample. The measured resolutions in the x (perpendicular to line focus) and y (parallel to line focus) directions are both $2{\mu}m$, with a 2X scan lens and a 3X relay lens. This optical system is useful for measuring defects, such as spalling, chipping, delamination, etc., on the surface of carbon fiber reinforced plastic (CFRP) holes after machining in conjunction with adjustments in the angle of LED lighting. Defects on the inner wall of holes are measured by line confocal laser scanning. This confocal method will be useful for analyzing defects after CFRP machining and for fast 3D image reconstruction.

• 반도체디스플레이기술학회지
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• 제9권2호
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• International Journal of Precision Engineering and Manufacturing
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• 제7권3호
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• pp.18-23
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• 2006

The formation degree of sustain (ITO pattern) determines the quality of a PDP (Plasma Display Panel). Thus, in the present study, we attempt to detect 100% of the defects that are larger than $30{\mu}m$. Currently, the inspection method in the PDP manufacturing process is dependent upon the naked eye or a microscope in off-line mode. In this study, a prototype inspection system for PDP ITO patterned glass is developed. The developed system, which is based on a line-scan mechanism, obtains information on the defects and sorts the defects by type automatically. The developed inspection system adopts a multi-vision method using slit-beam formation for minimum inspection time and the detection algorithm is embodied in the detection ability. Characteristic defects such as pin holes, substances, and protrusions are extracted using the blob analysis method. Defects such as open, short, spots and others are distinguished by the line type inspection algorithm. It was experimentally verified that the developed inspection system can detect defects with reliability of up to 95% in about 60 seconds for the 42-inch PDP panel.

• 한국정밀공학회지
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• 제16권12호
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• pp.60-70
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• 1999

An efficient automatic inspection system for Floating Seal is developed, The proposed system consists of a high resolution line scan camera, microcomputer, and PLC (Programmable Logic Controller). In order to perform rapid inspection, The ROI (Region of Interest) is extracted from the original image. There are types of defects; shape defects and surface defects. Each features of defects are captured by edge detect, segmentation, morphological operation, and threshold analysis. PLC controller is used to synchronize the whole system and store the inspection results temporarily to reduce the overhead of microcomputer. As a result, the system is being utilized successfully in a teal inspection line.

• 제어로봇시스템학회논문지
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• 제3권4호
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• pp.406-414
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• 1997

A real-time inspection system is developed using line scan cameras. Several improved algorithms are proposed for real-time detection of defects in this automated inspection system. The major improved algorithms include the preprocessing, the threshold decision, and the clustering algorithms. The preprocessing algorithms are for exact binarization and the threshold decision algorithm is for fast detection of defects in 1-D binary images. The clustering algorithm is also developed for fast classifying of the defects. The system is applied to PCBs(Printed Circuit Boards) inspection. The typical defects in PCBs are pits, dent, wrinkle, scratch, and black spots. The results show that most defects are detected and classified successfully.

• 반도체디스플레이기술학회지
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• 제11권2호
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• pp.45-51
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• 2012

Multilayer co-extrusion blown film construction is a popular technique for producing plastic films for various packaging industries. Automated detection of defective films can improve the quality of film production process. In this paper, we propose a film inspection system that can detect and classify film defects robustly. In our system, first, film images are acquired through a high speed line-scan camera under an appropriate lighting system. In order to detect and classify film defects, an inspection algorithm is developed. The algorithm divides the typical film defects into two groups: intensity-based and texture-based. Intensity-based defects are classified based on geometric features. Whereas, to classify texture-based defects, a texture analysis technique based on local binary pattern (LBP) is adopted. Experimental results revealed that our film inspection system is effective in detecting and classifying defects for the multilayer co-extrusion blown film construction line.

• 한국기계가공학회지
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• 제17권1호
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• pp.95-100
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• 2018

This study has focused on the weld-line and birefringence reduction of a plastic optic lens using over and CAE analysis in injection compression molding. A concave lens, which has a thin thickness in the center and a large difference in thickness between the center and the periphery, often causes weld-line defects during injection molding. CAE analysis has been applied to optimize the overflow design in order to reduce the weld-line defects and the polarization defects. To reduce the weld line and birefringence defects, overflow design and application using CAE analysis show that the measured birefringence values of the specimens before the overflow application were 46.8nm and 36.9nm, and the values after the over-flow application were 13.6nm and 14.0nm. From the experimental results, it is confirmed that birefringence is greatly improved when overflow is applied.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1999년도 제3회 압연심포지엄 논문집 압연기술의 미래개척 (Exploitation of Future Rolling Technologies)
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• pp.412-422
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• 1999

Scale defects generated on the strip surface in a tandem finishing mill line are collected from the strip trapped among the production mills by freezing the growing scale on the strip by the melt glass coating and shutting down the line simultaneously. The samples observed of its cross sectional figure showed the process of scale defect formation where the defects are formed at the base metal surface by thicker oxidized scale during each rolling passes. The properties of the oxidized layer growth both at rolling and inter-rolling are detected down sized rolling test simulating carefully the rolling condition of the production line. The thickness of the oxidized layer at each rolling pass are simulated numerically. The critical scale thickness to avoid the defect formation is determined through the expression of mutual relation between oxidized layer thickness and the lanks of the strip called quality for the scale defects. The scale growth of scale less than the critical thickness and also to keep the bulk temperature tuning the water flow rate and cooling time appropriately. Two units of Inerstand Cooler are designed and settled among the first three stands in the production line. Two units of scale defect is counted from the recoiled strip and the results showed distinct decrease of the defects comparing to the conventionaly rolled products.

• Agricultural and Biosystems Engineering
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• 제4권1호
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• pp.1-7
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• 2003

Internal defects such as browning of the flesh and blackening and rot of the ovary of pear can be easily developed because of the inadequate environmental conditions during the storage and distribution of fruit. The quality assurance system for the agricultural product is to be settled in Korea. All defected agricultural products should be excluded prior to the distribution to enhance the commercial values. However, early stage on-line defect detection of agricultural product is very difficult and even more difficult in a case of the internal defects. The goal of this research is to develop a system that can detect and classify internal defects of agricultural produce on-line using VIS/NIR transmittance spectroscopy. And Shingo pear, which is one of the famous species of Korean pear, was used for the experiment. Soft independence modeling of class analogy (SIMCA) algorithm was employed to analyze the transmittance spectroscopic data qualitatively. On-line classification system was constructed and classification model was developed and validated. As a result, the correct classification rate (CCR) using the developed classification model was 96.1 ％.