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Erschienen in: The International Journal of Advanced Manufacturing Technology 7-8/2022

14.09.2022 | ORIGINAL ARTICLE

Fast compensation of spatial PDGE of five-axis machine tools based on error parameter optimization

verfasst von: Weishu Song, Peiqing Ye, Hui Zhang, Bingran Li

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 7-8/2022

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Abstract

The machine tool used in the actual production line cannot be processed with high accuracy for a long time due to insufficient rigidity and poor accuracy retention. Thus, the calibration cycle of the machine tool must be shortened to ensure that the machine tool remains in a high accuracy state. To avoid unnecessary effects on the working time of the machine tool, the calibration method needs to improve the efficiency on the premise of ensuring high accuracy. In this study, a fast compensation method of the spatial position-dependent geometric error (PDGE) of five-axis machine tools based on error parameter optimization is proposed. The actual physical meaning of the position-related error and the mathematical calculation results of the influence on the tool position and attitude are studied, the optimized error parameter comprehensive representation model is established. Then, the translation axis four-line space compensation (TFSC) method and the rotational axis double line space compensation (RDSC) method are proposed, and the integrated algorithm module of the CNC system is developed. Experiments on five-axis machine tools show that the optimal parameter model and the fast compensation method proposed in this research significantly improve the compensation accuracy and efficiency.

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Metadaten
Titel
Fast compensation of spatial PDGE of five-axis machine tools based on error parameter optimization
verfasst von
Weishu Song
Peiqing Ye
Hui Zhang
Bingran Li
Publikationsdatum
14.09.2022
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 7-8/2022
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-022-10072-y

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