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A Study on Gas Flow Visualization Inside the Thermal Cutting Kerf
Dae-Won Cho,Upendra Tuladhar,Sang-Hyun Ahn,Dae-Hwan Kim,Seokyoung Ahn,Seonmin Kim,Seung-Hoon Bae,Tae-Kook Park 한국방사성폐기물학회 2022 한국방사성폐기물학회 학술논문요약집 Vol.20 No.1
In thermal cutting process, gas flow injected from the nozzle has a significant effect on the cutting materials. The gas flow is difficult to observe gases are transparent, therefore, in this study, Schlieren method was adopted to visualize the gas flow inside the kerf. The kerf shape was inserted between two slices of transparent glass in order to imitate the real cutting environment. In order to get the flow characteristics, a high speed camera was equipped and the image processing was applied to compare the before and after injection images. As a result, the method for visualizing gas flow was successfully developed and also expected to be applied to the analysis of purging gas in various welding environments.
박홍석(Hong-Seok Park),우펜드라 마니 툴라다르(Upendra Mani Tuladhar),신승철(Seung-Cheol Shin) 한국생산제조학회 2013 한국생산제조학회지 Vol.22 No.3
Over the past several years, many studies have been carried out in the field of 3D data inspection systems. Several attempts have been made to improve the quality of manufactured parts. The introduction of laser sensors for inspection has made it possible to acquire data at a remarkably high speed. In this paper, a robust inspection technique for detecting defects in 3D pressed parts using laser-scanned data is proposed. Point cloud data are segmented for the extraction of features. These segmented features are used for shape matching during the localization process. An iterative closest point (ICP) algorithm is used for the localization of the scanned model and CAD model. To achieve a higher accuracy rate, the ICP algorithm is modified and then used for matching. To enhance the speed of the matching process, a Kd-tree algorithm is used. Then, the deviation of the scanned points from the CAD model is computed.