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All position-independent and position-dependent geometric error measurement and identification of the precision of a horizontal boring machine tool.

Authors :
Guo, Shijie
Tang, Shufeng
Wu, Jianxin
Qiao, Guan
Source :
International Journal of Advanced Manufacturing Technology. Aug2022, Vol. 121 Issue 9/10, p6453-6473. 21p.
Publication Year :
2022

Abstract

Geometric error is the main obstacle that affects the quasi-static accuracy of horizontal boring machine tools. To improve quasi-static performance, the error terms of all position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs) must be measured and identified precisely. This study proposes a novel method for measuring and identifying the above two types of geometric errors based on double ballbar for the rotary axis. The error terms of the linear axis are identified from the measurement model based on the exponential product method and a preset measure trajectory, and the measure coordinate system is combined with the reference coordinate to lower the uncertainty in the identification accuracy. Then, the elastic net method and improved weight function IGG3-LTS method are established to identify the PIGEs and PDGEs of the rotary and linear axes, respectively. This method has the advantage that measurement with the built-in sensor method synchronously does not interfere with the running state of the machine tool, and neither the inaccuracy of reference-frame misalignment nor installation error of the measuring instrument affects the geometric error identification results of the linear axis. Moreover, all PIGEs and PDGEs, particular to the rotary axis of the horizontal boring machine tool, are determined accurately. The measurement and identification strategy is demonstrated by experimental comparison on a four-axis precision horizontal boring machine tool. The minimum compensation rate of each precision index of the test specimen is 40.0%, the average compensation rate is 52.7%, and the maximum compensation rate is 62.5%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
121
Issue :
9/10
Database :
Academic Search Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
158386118
Full Text :
https://doi.org/10.1007/s00170-022-09710-2