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Proceedings Paper

The partial least-squares regression analysis of impact factors of coordinate measuring machine dynamic error
Author(s): Mei Zhang; Yetai Fei; Li Sheng; Xiushui Ma; Hong-tao Yang
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Paper Abstract

The reasons why the coordinate measuring machine (CMM) dynamic error exists are complicate. And there are many elements which influence the error. So it is hard to build an accurate model. For the sake of attaining a model which not only avoided analyzing complex error sources and the interactions among them, but also solved the multiple colinearity among the variables. This paper adopted the Partial Least-Squares Regression (PLSR) to build model. The model takes 3D coordinates (X, Y, Z) and the moving velocity as the independent variable and takes the CMM dynamic error value as the dependent variable. The experimental results show that the model can be easily explained. At the same time the results show the magnitude and direction of the independent variable influencing the dependent variable.

Paper Details

Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304U (31 December 2008); doi: 10.1117/12.819734
Show Author Affiliations
Mei Zhang, Hefei Univ. of Technology (China)
Anhui Univ. (China)
Yetai Fei, Hefei Univ. of Technology (China)
Li Sheng, Hefei Univ. of Technology (China)
Xiushui Ma, Zhejiang Univ. (China)
Hong-tao Yang, Anhui Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

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