Experimental Study on the Effectiveness of Two Different Geometric Error Modeling Methods for Machine Tools

doi:10.3901/JME.2019.05.137

Abstract

Abstract: Machine tools are widely used in manufacturing whose geometric accuracy has important influences on the accuracy of workpieces. Error compensation of machine tool translation axis is an important method to achieve high geometrical accuracy for machine tools, in which geometric modeling lays the foundation. There are two error modeling methods are usually used, i.e., error modeling based on 18 and 21 error components respectively. Error compensation which consist of error measuring, error identification and error compensation is usually based on these two kinds of models. And the different effects of error compensations based on the two kinds of models have not been systematically studied. However, the differences would bring different influences, which are quite important for realizing better error compensation effects. Based on identification and compensation, two different geometric error models are systematically analyzed and compared by studying the simulation and experiment of the error measuring. Described by 18-error model, the 3-axis machine tool has 18 geometric errors, while described by 21-error model it has 18 geometric errors in which there are three extra angular errors resulting in the distortion of the error prediction model. Furthermore, the simulation and experiments results of error compensation also show that the error model with 18 geometric error components is better in error compensation. The study can bring a clear suggestion for the error compensation method by using software.

Key words: effectiveness, error compensation, error model, experimental verification, geometric error modeling method, machine tool

CLC Number:

TG156

DONG Zeyuan, LI Jie, LIU Xinjun, MEI Bin, CHEN Junyu. Experimental Study on the Effectiveness of Two Different Geometric Error Modeling Methods for Machine Tools[J]. Journal of Mechanical Engineering, 2019, 55(5): 137-147.

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