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볼엔드 밀링에서의 일정 절삭력을 위한 NURBS 곡면 인터폴레이터
지성철,구태훈,Ji, Seong-Cheol,Gu, Tae-Hun 대한기계학회 2002 大韓機械學會論文集A Vol.26 No.9
This study presents a new type of CNC interpolator that is capable of generating cutter paths for ball-end milling of NURBS surfaces. The proposed surface interpolator comprises real-time algorithms for cutter contact (CC) path scheduling and CC path interpolator. Especially in this study, a new interpolator module to regulate cutting forces is developed. This propose algorithm utilizes variable-feedrate commands along the CC path according to the curvature of machined surfaces during the interpolation process. Additionally, it proposes an OpenGL graphic library for computer graphics and animation of interpolated tool-position display. The proposed interpolator is evaluated and compared with the existing method based on constant feedrates through computer simulations.
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지성철,유상필,Ji, Seong-Cheol,Yu, Sang-Pil 대한기계학회 2002 大韓機械學會論文集A Vol.26 No.8
In this study, the cross-coupling control (CCC) with three new features is proposed to maintain contour precision in high-speed nonlinear contour machining. One is an improved contour error model that provides almost exact calculation of the errors. Another is the utilization of variable controller gains based on the instantaneous curvature of the contour and the variable command. For this scheme, a stability is analyzed. As a result, the stability region is obtained, and the variable gains are decided within that region. The other scheme in the proposed CCC is a real-time feedrate adaptation module to regulate cutting force fur better surface finish through regulation of material removal rate (MRR). The simulation results show that the proposed CCC system can provide better precision than the existing method particularly in high-speed machining of nonlinear contours.
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지성철(Seong Cheol Ji),강선우(Sun Woo Kang),김준식(Joon Seek Kim),주효남(Hyonam Joo) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.12
A camera-based real-time hand posture and gesture recognition system is proposed for controlling various devices inside automobiles. It uses an imaging system composed of a camera with a proper filter and an infrared lighting device to acquire images of hand-motion sequences. Several steps of pre-processing algorithms are applied, followed by a background normalization process before segmenting the hand from the background. The hand posture is determined by first separating the fingers from the main body of the hand and then by finding the relative position of the fingers from the center of the hand. The beginning and ending of the hand motion from the sequence of the acquired images are detected using pre-defined motion rules to start the hand gesture recognition. A set of carefully designed features is computed and extracted from the raw sequence and is fed into a decision tree-like decision rule for determining the hand gesture. Many experiments are performed to verify the system. In this paper, we show the performance results from tests on the 550 sequences of hand motion images collected from five different individuals to cover the variations among many users of the system in a real-time environment. Among them, 539 sequences are correctly recognized, showing a recognition rate of 98%.
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