Journal
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
Volume 50, Issue 3, Pages 270-280Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ijmachtools.2009.11.010
Keywords
Cross Grid Encoder; Geometric motion error; Modeling; Sequential identification; CNC Machine tool
Funding
- National Natural Science Foundation of China [50805094]
- National Basic Research Program of China [2006CB705400]
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Machining accuracy is directly influenced by the quasi-static errors of a machine tool. Since machine errors have a direct effect on both the surface finish and geometric shape of the finished work piece, it is imperative to measure the machine errors and to compensate for them. A revised geometric synthetic error modeling, measurement and identification method of 3-axis machine tool by using a cross grid encoder is proposed in this paper. Firstly a revised synthetic error model of 21 geometric error components of the 3-axis NC machine tools is developed. Also the mapping relationship between the error component and radial motion error of round work piece manufactured on the NC machine tools are deduced. Aiming to overcome the solution singularity shortcoming of traditional error component identification method, a new multi-step identification method of error component by using the cross grid encoder measurement technology is proposed based on the kinematic error model of NC machine tool. Finally the experimental validation of the above modeling and identification method is carried out in the 3-axis CNC vertical machining center Cincinnati 750 Arrow. The entire 21 error components have been successfully measured by the above method. The whole measuring time of 21 error components is cut down to 1-2 h because of easy installation, adjustment, operation and the characteristics of non-contact measurement. It usually takes days of machine down time and needs an experienced operator when using other measuring methods. Result shows that the modeling and the multi-step identification methods are very suitable for 'on machine' measurement. (C) 2009 Elsevier Ltd. All rights reserved.
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