The partial least-squares regression analysis of impact factors of coordinate measuring machine dynamic error

Mei Zhang; Yetai Fei; Li Sheng; Xiushui Ma; Hong-tao Yang

doi:10.1117/12.819734

31 December 2008 The partial least-squares regression analysis of impact factors of coordinate measuring machine dynamic error

Mei Zhang, Yetai Fei, Li Sheng, Xiushui Ma, Hong-tao Yang

Author Affiliations +

Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71304U (2008) https://doi.org/10.1117/12.819734
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China

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.

Citation Download Citation

Mei Zhang, Yetai Fei, Li Sheng, Xiushui Ma, and Hong-tao Yang "The partial least-squares regression analysis of impact factors of coordinate measuring machine dynamic error", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304U (31 December 2008); https://doi.org/10.1117/12.819734

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