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다물체 동역학 조건을 고려한 다축 로봇 프레임 제너레이티브 디자인
이수민(Sumin Lee),김승규(Seunggyu Kim),강남우(Namwoo Kang) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
The lightweight and strength design of the robot frame has a significant impact on performance. Optimization via CAE facilitated design for a single part. However, in the case of a kinematic system consisting of multiple links, many trial and errors are required to use the existing design methods. This study constructs a framework for inverse design by learning the frames of the 4-bar link mechanism robot arm generated by parametric design through FEA. Each link used up to 14 design variables to generate massive data. As a result, a set of link combinations corresponding to boundary conditions with the stiffness values obtained through FEA automation can be used for deep learning.