A Corner Rounding and Trajectory Generation Algorithm for Five-axisLinear Toolpath

  • ZHAO Huan ,
  • ZHANG Yonghong ,
  • DING Han
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  • State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074

Received date: 2017-01-16

  Revised date: 2017-05-22

  Online published: 2018-02-05

Abstract

Linear tool paths are still the most widely used format of tool path in five-axis machining. Tangential and curvature discontinuities of linear tool path may lead to vibration of the machine, which inevitably result in poor machining efficiency and quality. To solve this issue, different smoothing methods is developed in the existing literatures. There exist some problems such as parameter synchronization, error restriction and real-time that cannot be realized simultaneously, the nonlinear kinematics are not taken into account while feedrate scheduling. A novel local path smoothing for five-axis machine is proposed. Segment junctions of the linear tool path in the workpiece coordinate system are blended by two transition cubic-Bézier curves. One cubic Bézier curve is used to smooth the segment junction of tool tip position path. To ensure magnitude of the orientation vector always results in unit magnitude, it is represented by two Eular angles and mapped form spherical coordinates to Cartesian plane, where another Bézier curve is used. Then, a trajectory generation algorithm for local path smoothing is proposed. The proposed trajectory generation algorithm takes the nonlinear kinematics into account, and look-ahead and seven segment S-shape feedrate scheduling method is employed to schedule a feedrate profile while respecting drive constrains. Finally, the experiments are conducted to verify the feasibility and efficiency of the proposed algorithm.

Cite this article

ZHAO Huan , ZHANG Yonghong , DING Han . A Corner Rounding and Trajectory Generation Algorithm for Five-axisLinear Toolpath[J]. Journal of Mechanical Engineering, 2018 , 54(3) : 108 -116 . DOI: 10.3901/JME.2018.03.108

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