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TECHNICAL PAPERS

Dynamic Modeling for Machine Tool Thermal Error Compensation

[+] Author and Article Information
Hong Yang, Jun Ni

S.M. Wu Manufacturing Research Center, University of Michigan, Ann Arbor, MI 48109

J. Manuf. Sci. Eng 125(2), 245-254 (Apr 15, 2003) (10 pages) doi:10.1115/1.1557296 History: Received February 01, 2001; Revised November 01, 2002; Online April 15, 2003
Copyright © 2003 by ASME
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References

Venugopal,  R., and Barash,  M., 1986, “Thermal Effects on the Accuracy of Numerically Controlled Machine Tools,” CIRP Ann., 35(1), pp. 255–258.
Donmez,  M. A., Liu,  C. R., and Barash,  M. M., 1986, “General Methodology for Machine Tool Accuracy Enhancement by Error Compensation,” Precis. Eng., 8(4), pp. 187–196.
Yang,  S., Yuan,  J., and Ni,  J., 1996, “The Improvement of Thermal Error Modeling and Compensation on Machine Tools by Neural Network,” Int. J. Mach. Tools Manuf., 36(4), pp. 527–537.
Kurtoglu,  A., 1990, “The Accuracy Improvement of Machine Tools,” CIRP Ann., 39(1), pp. 417–419.
Donmez, M. A., 1991, “Progress Report of the Quality in Automation Project for FY90,” Technical Report NISTIR-4536, National Institute of Standards and Technology, Gaithersburg, MD.
Chen, J. S., Yuan, J., Ni, J., and Wu, S. M., 1992, “Thermal Error Modeling for Volumetric Error Compensation,” Proceedings, 1992 ASME Winter Annual Meeting, PED-Vol. 55, pp. 113–125.
Lo, C., 1994, “Optimal Modeling of Thermal Error Components for Machine Tool Error Compensation,” S. M. Wu Symposium pp. 61–67.
McClure,  E. R., and Thal-Larson,  H., 1971, “Thermal Effects In Precision Machining,” J. Mech. Eng., 93(7), pp. 11–14.
Moriwaki,  T., and Shamoto,  E., 1998, “Analysis of Thermal Deformation of an Ultraprecision Air Spindle System,” CIRP Ann., 47(1), pp. 315–319.
Li,  S., Zhang,  Y., and Zhang,  G., 1997, “A Study of Pre-compensation for Thermal Errors of NC Machine Tools,” Int. J. Mach. Tools Manuf., 37(12), pp. 1715–1719.
Stein,  J. L., and Tu,  J. F., 1994, “A State-Space Model for Monitoring Thermally Induced Preload in Anti-Friction Spindle Bearings of High-Speed Machine Tools,” ASME J. Dyn. Syst., Meas., Control, 116(3), pp. 372–386.
Wang,  Y., Zhang,  G. , 1998, “Compensation for the Thermal Error of a Multi-axis Machining Center,” J. Mater. Process. Technol., 75(1), pp. 45–53.
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Fraser,  S., Attia,  M. H., and Osman,  M. O. M., 1998, “Modeling, Identification and Control of Thermal Deformation of Machine Tool Structures, Part I: Concept of Generalized Modeling,” ASME J. Manuf. Sci. Eng., 120(3), pp. 623–631.
Ljung, L., 1999, System Identification: Theory for the User, Prentice Hall PTR.
Bayoumi,  M. M., Wong,  K. Y., and El-Bagoury,  M. A., 1981, “A Self-Turning Regulator for Multivariable Systems,” Automatica, 17(4), pp. 575–592.
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Figures

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Pseudo-hysteresis effect of thermoelastic deformation (‘[[dashed_line]]’ warm up stage; ‘–’ cool down stage)
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The spatial relationship of temperature distribution along the spindle
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The partition of the main model into submodels
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Finite element model of the spindle
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Heat flux input data for modeling and model cross validation
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Input and output modeling data for 1-D spindle thermal deformation
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Thermal deformation vs. temperature relationship for the modeling data
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Thermal deformation response for the modeling data
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Thermal deformation vs. temperature—model cross validation
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Thermal deformation response for the model validation data
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2-D FEA model of the machine structure
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Heat flux input data of three heat sources for (a) modeling (b) model validation
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Three point temperature responses and two direction thermal deformations
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Simulated system output and model estimation output for X and Y directional thermal drifts using modeling data: (a) OE 220 model (b) stepwise linear regression model. (‘[[dotted_line]]’ is the simulated system output; ‘–’ is the model output)
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Simulated system output and model estimation output for X and Y directional thermal drifts using model validation data: (a) OE 220 model (b) stepwise linear regression model. (‘[[dotted_line]]’ is the simulated system output; ‘–’ is the model output)
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Scheme of spindle thermal experiment setup
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Spindle speed, temperature measurements and spindle elongation diagrams for: (a) modeling data, (b) model validation data #1, (c) model validation data #2
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Comparison of measured system output and OE250 model output for modeling data and model validation data

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