4.7 Article

An analytical local corner smoothing algorithm for five-axis CNC machining

期刊

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijmachtools.2017.07.007

关键词

Tool path; Corner smoothing; Five-axis; CNC machining; Interpolation

资金

  1. National Natural Science Foundation of China (NSFC) [51505167, 51535004]
  2. SERC CANRIMT2 Strategic Research Network
  3. China Postdoctoral Council

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Linear motion commands of computer numerical control (CNC) machine tools need to be smoothed at the transition corners in order to guarantee continuous and steady machining. However, because of the complex kinematic constraints, very few researches have devoted to developing analytical and high order continuous corner smoothing algorithms of five-axis tool paths, although it is important to guarantee both high calculation efficiency and good dynamic performance of five-axis CNC machining. This paper develops an analytical C-3 continuous corner smoothing algorithm of five-axis tool paths by locally inserting specially designed quintic micro splines into the transition corners of five-axis linear commands. C-3 continuity of the tool tip position and the tool orientation are guaranteed along the entire tool path. The maximal approximation errors of the tool tip position and the tool orientation are both constrained in the workpiece coordinate system. The synchronization of the tool tip position and tool orientation are mathematically guaranteed at the junctions of the linear and spline segments. The proposed corner smoothing algorithm can calculate all control points of the locally inserted tool tip position and tool orientation splines analytically without any iteration, which makes it very suitable to on-line calculation. Experiments on an in-house developed five-axis CNC platform verify that the maximal approximation errors of both tool tip position and tool orientation are constrained, and the proposed C-3 continuous corner smoothing algorithm has higher tracking accuracy and lower acceleration frequency content at higher frequencies than the C-2 continuous algorithm.

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