Thermal Behavior Regression Analysis for Dual Linear Feed Drive Mechanism with Self-Tuning PLS

Abstract:

Gantry dual direct drive mechanism has lots of advantages in translation process for large-sized high speed machine tools. In order to explore the temperature factors inducing thermal deformation behavior of the mechanism, a methodology with self-tuning partial least squares (PLS) linear regression was brought forward to analyze the thermal process on the basis of experiments with a system of thermocouples and interferometer. Temperature variations from the points where the thermocouples were attached were screened intelligently with genetic algorithm in the regression calculations. With the resultant self-tuning PLS regression, the relations between temperature distribution characteristics of those a few screened points and thermal errors were explored in a discussion. The test results from this obtained regression model show that the proposed method can effectively filter the multiple correlations of the temperature variables and reach high identification accuracy. As a result, the study provides a theoretical foundation for both better design of the mechanism and online error compensation requirement.

• Periodical: Advanced Materials Research (Volumes 834-836)
• Pages: 1205-1209
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.834-836.1205
• Online since: October 2013
• Authors: Xian Kun Lin, Qian Qian Wu
• Keywords: Feed Drive Mechanism, Linear Motor, Partial Least Square, Thermal Distortion Error

References

[1] Xiaoli Li, R. Du, Berend Denkena: Tool breakage monitoring using motor current signals for machine tools with linear motors. IEEE Transaction on Industrial Electronics. Vol. 52(2005), No. 5, pp.1403-1408.

DOI: 10.1109/tie.2005.855656

[2] C. Jang, J. Kim and Y. Kim: Thermal resistance modeling of linear motor driven stages for chip mounter applications, in 2002 Proc. 8th Intersociety Conf. Thermal and Thermo-mechanical Phenomena in Electronic Systems, (2002), pp.77-84.

DOI: 10.1109/itherm.2002.1012441

[3] J. Bryan, International status of thermal error research, Ann. CIRP 1990, 39 (2): 645–656.

DOI: 10.1016/s0007-8506(07)63001-7

[4] Z.Z. Xu, X.J. Liu, H.K. Kim: Thermal error forecast and performance evaluation for an air-cooling ball screw system. International Journal of Machine Tools & Manufacture, Vol. 5 (2011), pp.605-611.

DOI: 10.1016/j.ijmachtools.2011.04.001

[5] I. U. EUN: Comparison between asynchronous and synchronous linear motors as to thermal behavior, International Journal of the Korean Society of Precision Engineering, Vol. 2(2001), No. 3, pp.61-68.

[6] R, Y. H. Jeong and D. W. Cho: Thermal behavior of a machine tool equipped with linear motors, International Journal of Machine Tools and Manufacture, Vol. 44(2004), No. (7-8), pp.749-758.

DOI: 10.1016/j.ijmachtools.2004.02.006

[7] Ruilan Liu, Weiquan Chen: Optimal selection of secondary variables based on GA-PLS algorithmand its application to soft sensor modeling. Journal of Nan Jing University of Posts and Telecomm unications，Vol. 26(2006), No. 1, pp.77-78.

[8] Huiwen Wang，Zaibin Wu and Jie Meng: Partial Least-Squares Regression—Linear and Nonlinear Methods, National Defense Industry Press, Beijing, BJ(2006).

[9] Guangnan Xuan, Runwei Chen and Xinjie Yu: Genetic Algorithms and Engineering Optimization, Tsinghua University press, Beijing, BJ(2004).

[10] OPTODYNE, INC. Laser Doppler displacement meter user's guide MCV-500 (2005).