• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.4 no.2
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• pp.46-49
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• 2008

NDE(Nondestructive examination) detects a flaw or discontinuity in materials. Flaws detected by the pre-service or in-service examinations shall be sized for the purpose of analysis and repair. A flaw that is initiated from the surface is difficult to determine its depth by NDE. The depth of the surface flaw can be measured using an ultrasonic diffracted wave. To find the optimum standard for ultrasonic parameter(For example, frequency & size of transducer), a mock-up test and simulation were established and studied. This inspection technology may show the depth sizing possibility of the flaw down to nearly two(2) mm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.627-632
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• 2016

In this paper, we propose a new vision-based defect inspection system for the surface of hot slabs. To minimize the influence of self-emission from slab surfaces with high temperature, an optic method based on blue LED light and a blue pass filter is proposed. Because the slab surface is partially covered with scales, which are unavoidable oxidized substances caused during manufacturing, it is difficult to distinguish between vertical cracks and scale. In order to resolve this problem and to improve the detection performance, the use of a Gabor filter and dynamic programming are proposed. Finally, the effectiveness of the proposed method is shown by means of experiments conducted on images of hot slabs that were obtained from an actual slab production line.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.2
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• pp.4-9
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• 2013

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.20 no.1
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• pp.31-37
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• 2016

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.28-33
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• 2008

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.11
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• pp.63-68
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• 2019

The dimensional quality of flexible foams is often difficult to be evaluated through general machine vision inspection methods due to the free deformation of the outer shape. For the evaluation of the dimensions of flexible foams, methods of estimating the size of the product through the expansion rate of the product surface are evaluated. Specimens with various dimensions and surface gratings are prepared, and the degree of surface expansion is measured through machine vision. The correlation, between the measured surface grid size and the actual size of test specimens, is analyzed. We further analyze the correlation between the size of test specimens and the position of the surface grid. This study provides a basis for estimating the actual dimensions of specimens by measuring the surface expansion of flexible foams.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.73-84
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• 1995

New morphological positioning algorithm and inspection method are presented and compared with a method by means of the Hough transform. The positioning algorithm is the process of finding the center and the rotated angle of the surface mounted device (SMD). The inspection method is capable of detecting the location of broken or bent leads. In order to obtain the center and the orientation of the SMD rapidly, the Hough transform method utilizes feature points (concave points) and is executed on a DSP board. The proposed morphological method is implemented by using the morphological skeleton subsets, and an ultimate orientation is decided by the Hit-or-Miss transform (HMT). In the inspection process, two inspection methods also are presented. The first method utilizes the morphological methods, i.e., opening and closing. It is performed before the positioning process and called an initial inspection. The second method follows the positioning process and is performed by an inspection of intersections of rulers and the lead edge (or the skeleton). It is a ruling technique which is referred to as a detailed inspection. We find the morphological approach is preciser and faster than the Hough approach by the comparison of the proposed algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.573-577
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• 2002

A tape feeder of a SMD(Surface Mount Device) mounter is a device that sequentially feeds electronic components on a tape reel to the pick-up system of the mounter. As components are getting much smaller, feeding accuracy of a feeder becomes one of the most important factors for successful component pick-up. Therefore, it is critical to keep the feeding accuracy to a specified level in the assembly and production of tape feeders. This paper describes a tape feeder inspection system that was developed to automatically measure and inspect feeding accuracy using machine vision. It consists of a feeder base, an image acquisition system, and a personal computer. The image acquisition system is composed of CCD cameras with lens, LED illumination systems, and a frame grabber inside the PC. This system loads up to six feeders at a time and inspects them automatically and sequentially. The inspection software was implemented using Visual C++on Windows NT with easily usable GUI. Using this system, we can automatically measure and inspect the quality of all feeders in production process by analyzing the measurement results statistically.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.