• 한국산학기술학회논문지
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• 제20권12호
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• pp.390-397
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• 2019

현대 제조 공업이 고효율, 고정밀도와 경제적인 방향으로 발전 하면서 금속을 절단하는 띠톱 기계는 이미 철강, 기계, 자동차, 조선, 석유, 광산, 항공 우주 등 다양한 영역에서 광범위 하게 활용 되고 있다. 하지만 기존의 띠톱 기계들은 경험적으로 설계 되어져 왔으며 따라서 낮은 수명, 톱질 동작 상태에서 낮은 정밀도 및 저효율을 문제와 높은 제조원가 문제를 가지고 있다. 본 논문에서는 띠톱의 역학적 해석을 통해 띠톱 톱대의 설계 파라미터를 개선하는 방법을 제시 하였다. 실제로 빈번하게 사용 되고 있는 띠톱 기계를 모델링 하여 응력 분석, 피로해석을 시행 하였으며 이에 따라 톱대의 상세한 설계 파라미터를 도출 하였다. 그 결과 피로 강도가 피로 요구 사항을 만족 시키고 띠톱 기계의 정밀도와 효율이 크게 향상 되는 것을 확인할 수 있었다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 춘계 학술논문 발표대회
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• pp.247-248
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• 2018

In order to secure the variability of long-life housing, dry walls are used. The composite gypsum board panel is the most frequently used infill system for the wall, and it is an excellent construction method in terms of constructability and economic feasibility. However, there are also problems such as the destruction of Ondol pipes at the bottom floor and being unable to fix the light weight steel frame (M-bar) when a variable composite gypsum board panel is used. To solve such problems, a wall with a method of fixing only the top part without fixing the bottom floor is developed, but it is difficult to identify the durability of ceiling frame according to the tensile force of stud and the safety according to the Stiffness and impact resistance (soft body) of ceiling frame. Therefore, this study verified the effectiveness of infill system for the wall by conducting experiment on the stiffness and impact resistance of composite gypsum board panel according to the reinforcement of ceiling frame (wooden frame, double saw-toothed bracket, Cross M-bar). As a result, it was possible to secure the safety of wooden frame while the impact resistance and the Stiffness of double saw-toothed bracket and cross M-bar were not secured.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.237-250
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• 2015

This paper describes a hardware-oriented algorithm and its conceptual implementation in a real-time speed limit traffic sign detection system on an automotive-oriented field-programmable gate array (FPGA). It solves the training and color dependence problems found in other research, which saw reduced recognition accuracy under unlearned conditions when color has changed. The algorithm is applicable to various platforms, such as color or grayscale cameras, high-resolution (4K) or low-resolution (VGA) cameras, and high-end or low-end FPGAs. It is also robust under various conditions, such as daytime, night time, and on rainy nights, and is adaptable to various countries' speed limit traffic sign systems. The speed limit traffic sign candidates on each grayscale video frame are detected through two simple computational stages using global luminosity and local pixel direction. Pipeline implementation using results-sharing on overlap, application of a RAM-based shift register, and optimization of scan window sizes results in a small but high-performance implementation. The proposed system matches the processing speed requirement for a 60 fps system. The speed limit traffic sign recognition system achieves better than 98% accuracy in detection and recognition, even under difficult conditions such as rainy nights, and is implementable on the low-end, low-cost Xilinx Zynq automotive Z7020 FPGA.