Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6867746 | Robotics and Computer-Integrated Manufacturing | 2018 | 13 Pages |
Abstract
Some of five-axis machine tools, which are widely used for micro-machining, have structural restrictions, such as the center line of tilting rotary axis being close to the surface of worktable or beneath the worktable. In this paper, simultaneous motions of both rotary and translational axes are combined with double ball bar to establish a measurement and one installation-based method for identifying the position independent geometric errors (PIGEs) of rotary axes for this kind of five-axis machine tools. Due to the existence of structural restrictions, the tool ball usually cannot be placed in the center line of the tilting rotary axis, and thus, actual spatial motion of ball bar is considered in the proposed identification procedure. For each rotary axis, two test configurations, i.e. the one along the radial direction of rotary axis and the other along the axial direction, are proposed to carry out the designed measurement and identification. Especially, to well avoid the potential negative problems induced by structural restrictions, rotary and translational axes are simultaneously controlled to carry out the measurement, and in the identification procedure, eccentricities together with angle shift and setup errors are comprehensively involved. Based on this basic consideration, spatial plane, on which the actual trajectory of table ball lies, is accurately constructed to integrate the actual movement of ball bar into the PIGEs identification procedure. Novel fitting strategies are developed to mathematically model both the actual trajectory and the spatial plane of table ball's motion, which are then adopted to formulate the expressions for identifying location and orientation errors. Both simulation and experimental verifications show that the proposed method is effective and helpful for checking and improving the status of five-axis machine tools.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yang Liu, Min Wan, Wan-Jing Xing, Wei-Hong Zhang,