Thermal behavior analysis and thermal error compensation for motorized spindle of machine tools

International Journal of Precision Engineering and Manufacturing

Volumn 16, Issue 7, 2015, Pages 1571-1581

  Du, Zheng Chun ^a   Yao, Si Yu ^a   Yang, Jian Guo ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Error compensation; Machine tools; Motorized spindle; Natural Exponential Model (NEM); Thermal behavior analysis; Thermal error modeling

Indexed keywords

COST EFFECTIVENESS; DEFORMATION; MACHINE TOOLS; ROTATING MACHINERY;

EXPONENTIAL MODELS; MOTORIZED SPINDLE; PRECISION MACHINING; REAL-TIME COMPENSATIONS; THERMAL BEHAVIORS; THERMAL ERROR COMPENSATION; THERMAL ERROR MODELING; THERMAL FIELD DISTRIBUTION;

ERROR COMPENSATION;

EID: 84934903563     PISSN: 22347593     EISSN: 20054602     Source Type: Journal    
DOI: 10.1007/s12541-015-0207-x     Document Type: Article

References (35)

1. Bryan, J., “International Status of Thermal Error Research (1990),” CIRP Annals-Manufacturing Technology, vol. 39, no. 2, pp. 645–656, 1990.
2. Ramesh, R., Mannan, M., and Poo, A., “Error Compensation in Machine Tools-A Review: Part II: Thermal Errors,” International Journal of Machine Tools and Manufacture, vol. 40, no. 9, pp. 1257–1284, 2000.
3. Schwenke, H., Knapp, W., Haitjema, H., Weckenmann, A., Schmitt, R., and Delbressine, F., “Geometric Error Measurement and Compensation of Machines-An Update,” CIRP Annals- Manufacturing Technology, vol. 57, no. 2, pp. 660–675, 2008.
4. Lin, C. W., Lin, Y. K., and Chu, C. H., “Dynamic Models and Design of Spindle-Bearing Systems of Machine Tools: A Review,” Int. J. Precis. Eng. Manuf., vol. 14, no. 3, pp. 513–521, 2013.
5. Aramaki, H., Shoda, Y., Morishita, Y., and Sawamoto, T., “The Performance of Ball Bearings with Silicon Nitride Ceramic Balls in High Speed Spindles for Machine Tools,” Journal of Tribology, vol. 110, no. 4, pp. 693–698, 1988.
6. Choi, J. K., “Thermal Characteristics of the Spindle Bearing System with a Gear Located on the Bearing Span,” International Journal of Machine Tools and Manufacture, vol. 38, no. 9, pp. 1017–1030, 1998.
7. Bossmanns, B. and Tu, J. F., “A Power Flow Model for High Speed Motorized Spindles-Heat Generation Characterization,” Journal of Manufacturing Science and Engineering, vol. 123, no. 3, pp. 494–505, 2001.
8. Raja, V. P., Pillai, P. R., and Radhakrishnan, P., “Thermal Analysis of Spindle Units under High Speed Machining,” Journal-Institution of Engineers India Part MC Mechanical Engineering Division, pp. 155–159, 2001.
9. Yeo, S. H., Ramesh, K., and Zhong, Z. W., “Ultra-High-Speed Grinding Spindle Characteristics Upon using Oil/Air Mist Lubrication,” International Journal of Machine Tools and Manufacture, vol. 42, no. 7, pp. 815–823, 2002.
10. Kim, S. M. and Lee, S. K., “Prediction of Thermo-Elastic Behavior in a Spindle-Bearing System Considering Bearing Surroundings,” International Journal of Machine Tools and Manufacture, vol. 41, no. 6, pp. 809–831, 2001.
11. Kim, S. M., Lee, K. J., and Lee, S. K., “Effect of Bearing Support Structure on the High-Speed Spindle Bearing Compliance,” International Journal of Machine Tools and Manufacture, vol. 42, no. 3, pp. 365–373, 2002.
12. Lin, C. W., Tu, J. F., and Kamman, J., “An integrated Thermo-Mechanical-Dynamic Model to Characterize Motorized Machine Tool Spindles during very High Speed Rotation,” International Journal of Machine Tools and Manufacture, vol. 43, no. 10, pp. 1035–1050, 2003.
13. Li, H. and Shin, Y. C., “Analysis of Bearing Configuration Effects on High Speed Spindles using an Integrated Dynamic Thermo-Mechanical Spindle Model,” International Journal of Machine Tools and Manufacture, vol. 44, no. 4, pp. 347–364, 2004.
14. Holkup, T., Cao, H., Koláø, P., Altintas, Y., and Zelený, J., “Thermo- Mechanical Model of Spindles,” CIRP Annals-Manufacturing Technology, vol. 59, no. 1, pp. 365–368, 2010.
15. Xu, Z. Z., Liu, X. J., Choi, C. H., and Lyu, S. K., “A Novel High Speed/High Precision Ball Screw,” Int. J. Precis. Eng. Manuf., vol. 14, no. 1, pp. 165–167, 2013.
16. Xu, Z. Z., Liu, X. J., Choi, C. H., and Lyu, S. K., “A Study on Improvement of Ball Screw System Positioning Error with Liquid-Cooling,” Int. J. Precis. Eng. Manuf., vol. 13, no. 12, pp. 2173–2181, 2012.
17. Xu, Z. Z., Liu, X. J., and Lyu, S. K., “Study on Thermal Behavior Analysis of Nut/Shaft Air Cooling Ball Screw for High-Precision Feed Drive,” Int. J. Precis. Eng. Manuf., vol. 15, no. 1, pp. 123–128, 2014.
18. Ren Y. Q. and Yang J. G., “Research on On-Line Modeling Method of Thermal Error Compensation Model for CNC Machines,” Chinese Journal of Mechanical Engineering, vol. 39, no. 3, pp. 81–84, 2003.
19. Denkena, B., Schmidt, C., and Krüger, M., “Experimental Investigation and Modeling of Thermal and Mechanical Influences on Shape Deviations in Machining Structural Parts,” International Journal of Machine Tools and Manufacture, vol. 50, no. 11, pp. 1015–1021, 2010.
20. Li, Y. X., Tong, H. C., Cao, H. T., Zhang, H. T., and Yang, J. G., “Application of Time Series Analysis to Thermal Error Modeling on NC Machine Tools,” Journal of Sichuan University, vol. 38, no. 2, pp. 74–78, 2006.
21. Chen, J. S., Yuan, J. X., Ni, J., and Wu, S. M., “Real-Time Compensation for Time-Variant Volumetric Errors on a Matching Center,” Journal of Engineering for Industry, vol. 115, no. 4, pp. 472–479, 1993.
22. Pandit, S. M. and Wu, S. M., “Time Series and System Analysis with Applications,” Wiley New York, 1983.
23. Shen, J. H. and Yang, J. G., “Application of Partial Least Squares Neural Network in Thermal Error Modeling for CNC Machine Tool,” Key Engineering Materials, vol. 392, pp. 30–34, 2009.
24. Yang, H. and Ni, J., “Dynamic Neural Network Modeling for Nonlinear, Nonstationary Machine Tool Thermally Induced Error,” International Journal of Machine Tools and Manufacture, vol. 45, no. 4, pp. 455–465, 2005.
25. Yang, S., Yuan, J., and Ni, J., “The Improvement of Thermal Error Modeling and Compensation on Machine Tools by CMAC Neural Network,” International Journal of Machine Tools and Manufacture, vol. 36, no. 4, pp. 527–537, 1996.
26. Mize, C. D. and Ziegert, J. C., “Neural Network Thermal Error Compensation of a Machining Center,” Precision Engineering, vol. 24, no. 4, pp. 338–346, 2000.
27. Briceno, J. F., El-Mounayri, H., and Mukhopadhyay, S., “Selecting an Artificial Neural Network for Efficient Modeling and Accurate Simulation of the Milling Process,” International Journal of Machine Tools and Manufacture, vol. 42, no. 6, pp. 663–674, 2002.
28. Yan, J. and Yang, J., “Application of Synthetic Grey Correlation Theory on Thermal Point Optimization for Machine Tool Thermal Error Compensation,” The International Journal of Advanced Manufacturing Technology, vol. 43, no. 11–12, pp. 1124–1132, 2009.
29. Li, Y. X., Yang, J. G., Gelvis, T., and Li, Y. Y., “Optimization of Measuring Points for Machine Tool Thermal Error based on Grey System Theory,” The International Journal of Advanced Manufacturing Technology, vol. 35, no. 7–8, pp. 745–750, 2008.
30. Wang, K. C., “Thermal Error Modeling of a Machining Center using Grey System Theory and Adaptive Network-based Fuzzy Inference System,” Proc. of IEEE Conference on Cybernetics and Intelligent Systems, pp. 1–6, 2006.
31. Yang, H. and Ni, J., “Dynamic Modeling for Machine Tool Thermal Error Compensation,” Journal of Manufacturing Science and Engineering, vol. 125, no. 2, pp. 245–254, 2003.
32. Kim, B. S., Song, Y. C., and Park, C. H., “Robust Thermal Error Modeling and Compensation for a Nano Level Thermal Drift in a High Precision Lathe,” Int. J. Precis. Eng. Manuf., vol. 12, no. 4, pp. 657–661, 2011.
33. Li, J., Zhang, W., Yang, G., Tu, S., and Chen, X., “Thermal-Error Modeling for Complex Physical Systems: The-State-of-Arts Review,” The International Journal of Advanced Manufacturing Technology, vol. 42, no. 1–2, pp. 168–179, 2009.
34. Harris, T. A., “Rolling Bearing Analysis,” John Wiley & Sons, 3rd Ed., pp. 540–560, 1991.
35. Creighton, E., Honegger, A., Tulsian, A., and Mukhopadhyay, D., “Analysis of Thermal Errors in a High-Speed Micro-Milling Spindle,” International Journal of Machine Tools and Manufacture, vol. 50, no. 4, pp. 386–393, 2010.