The conception of the comprehensive thermal error of servo axes is given. Thermal characteristics of a preloaded ball screw on a gantry milling machine is investigated, and the error and temperature data are obtained. The comprehensive thermal error is divided into two parts: thermal expansion error ((TEE) in the stroke range) and thermal drift error ((TDE) of origin). The thermal mechanism and thermal error variation of preloaded ball screw are expounded. Based on the generation, conduction, and convection theory of heat, the thermal field models of screw caused by friction of screw-nut pairs and bearing blocks are derived. The prediction for TEE is presented based on thermal fields of multiheat sources. Besides, the factors influencing TDE are analyzed, and the model of TDE is established based on the least square method. The predicted thermal field of the screw is analyzed. The simulation and experimental results indicate that high accuracy stability can be obtained using the proposed model. Moreover, high accuracy stability can still be achieved even if the moving state of servo axis changes randomly, the screw is preloaded, and the thermal deformation process is complex. Strong robustness of the model is verified.

References

1.
Fu
,
J.
, and
Chen
,
Z.
,
2004
, “
Research on Identification of Thermal Dynamics Characteristics Parameter of Precision Machine Based on Singular Value Decomposition
,”
J. Zhejiang Univ.: Eng. Sci.
,
38
(
4
), pp.
474
476
.
2.
Ni
,
J.
,
1997
, “
CNC Machine Accuracy Enhancement Through Real-Time Error Compensation
,”
ASME J. Manuf. Sci. Eng.
,
119
(
4B
), pp.
717
725
.
3.
Han
,
Z. Y.
,
Jin
,
H. Y.
,
Liu
,
Y. L.
, and
Fu
,
H. Y.
,
2013
, “
A Review of Geometric Error Modeling and Error Detection for CNC Machine Tool
,”
Appl. Mech. Mater.
,
303–306
, pp.
627
631
.
4.
Wu
,
C. W.
,
Tang
,
C. H.
,
Chang
,
C. F.
, and
Shiao
,
Y. S.
,
2011
, “
Thermal Error Compensation Method for Machine Center
,”
Int. J. Adv. Manuf. Technol.
,
59
(
5–8
), pp.
681
689
.
5.
Zhu
,
J.
,
Ni
,
J.
, and
Shih
,
A. J.
,
2008
, “
Robust Machine Tool Thermal Error Modeling Through Thermal Mode Concept
,”
ASME J. Manuf. Sci. Eng.
,
130
(
6
), p.
061006
.
6.
Pajor
,
M.
, and
Zapłata
,
J.
,
2011
, “
Compensation of Thermal Deformations of the Feed Screw in a CNC Machine Tool
,”
Adv. Manuf. Sci. Technol.
,
35
(
4
), pp.
9
17
.http://advancesmst.prz.edu.pl/pdfy/01a-Pajr-Zapala.pdf
7.
Horejs
,
O.
,
Mares
,
M.
,
Kohut
,
P.
,
Barta
,
P.
, and
Hornych
,
J.
,
2010
, “
Compensation of Machine Tool Thermal Errors Based on Transfer Functions
,”
MM Sci. J.
,
3
, pp.
162
165
.https://www.researchgate.net/profile/Otakar_Horejs/publication/267202023_Compensation_of_machine_tool_thermal_errors_based_on_transfer_functions/links/566e8f5208ae62b05f0b546e.pdf?inViewer=0&pdfJsDownload=0&origin=publication_detail
8.
Lin
,
W.
,
Fu
,
J.
,
Chen
,
Z.
, and
Xu
,
Y.
,
2009
, “
Modeling of NC Machine Tool Thermal Error Based on Adaptive Best-Fitting WLS-SVM
,”
J. Mech. Eng.
,
45
(
3
), pp.
178
182
.
9.
Miao
,
E.
,
Gong
,
Y.
,
Xu
,
Z.
, and
Zhou
,
X.
,
2015
, “
Comparative Analysis of Thermal Error Compensation Model Robustness of CNC Machine Tools
,”
J. Mech. Eng.
,
51
(
7
), pp.
130
135
.
10.
Zhang
,
Y.
, and
Yang
,
J.
,
2011
, “
Modeling for Machine Tool Thermal Error Based on Grey Model Preprocessing Neural Network
,”
J. Mech. Eng.
,
47
(
7
), pp.
134
139
.
11.
Li
,
Y.
, and
Yang
,
J.
,
2006
, “
Application of Grey System Model to Thermal Error Modeling on Machine Tools
,”
China Mech. Eng.
,
17
(
23
), pp.
2439
2442
.
12.
Ozkan
,
M. T.
,
2013
, “
Experimental and Artificial Neural Network Study of Heat Formation Values of Drilling and Boring Operations on Al 7075 T6 Workpiece
,”
Indian J. Eng. Mater. Sci.
,
20
(
4
), pp.
259
268
.http://nopr.niscair.res.in/handle/123456789/20961
13.
Jin
,
Z. F.
, and
Wang
,
P.
,
2012
, “
Neural Network–Based Thermal Error Modeling in Ball Screw
,”
Modular Machine Tool and Automatic Manufacturing Technique
,
1
, pp.
67
70
.
14.
Liu
,
G.
,
Zhang
,
H.
,
Cao
,
H.
,
Zhao
,
H.
, and
Yang
,
J.
,
2005
, “
Study on the Application of the Neural Network Theories in the NC Machine Tool Error Modeling
,”
Modern Manuf. Eng.
,
8
(
8
), pp.
20
23
.
15.
Feng
,
W. L.
,
Li
,
Z. H.
,
Gu
,
Q. Y.
, and
Yang
,
J. G.
,
2015
, “
Thermally Induced Positioning Error Modeling and Compensation Based on Thermal Characteristic Analysis
,”
Int. J. Mach. Tool Manuf.
,
93
, pp.
26
36
.
16.
Liu
,
K.
,
Liu
,
Y.
,
Sun
,
M.
,
Wu
,
Y.
, and
Zhu
,
T.
,
2015
, “
Comprehensive Thermal Compensation of the Servo Axes of CNC Machine Tools
,”
Int. J. Adv. Manuf. Technol.
,
85
(
9
), pp.
2715
2728
.
17.
Chen
,
C.
,
Qiu
,
Z. R.
,
Li
,
X. F.
,
Dong
,
C. J.
, and
Zhang
,
C. Y.
,
2011
, “
Temperature Field Model of Ball Screws Used in Servo Systems
,”
Opt. Precis. Eng.
,
19
(
5
), pp.
1151
1158
.
18.
Liu
,
K.
,
Sun
,
M.
,
Wu
,
Y.
, and
Zhu
,
T.
,
2016
, “
Comparison of Accuracy Stability Using a Thermal Compensator and Grating Ruler
,”
J. Braz. Soc. Mech. Sci. Eng.
,
38
(
8
), pp.
1
9
.
19.
Zhang
,
J. Z.
, and
Chang
,
H. P.
,
2009
,
Heat Transfer
,
Science Press
,
Beijing, China
.
20.
Chen
,
C.
,
2010
, “
Structure Analysis and Research on Drive System Thermal Error Model of θFXZ Type CMMs
,” Tianjin University, Tianjin, China.
21.
Fraser
,
S.
,
Attia
,
M.
, and
Osman
,
M.
,
1998
, “
Modelling, Identification and Control of Thermal Deformation of Machine Tool Structures—Part I: Concept of Generalized Modelling
,”
ASME J. Manuf. Sci. Eng.
,
120
(
3
), pp.
623
631
.
22.
Horejs
,
O.
,
2007
, “
Thermo-Mechanical Model of Ball Screw With Non-Steady Heat Sources
,” International Conference on Thermal Issues in Emerging Technologies: Theory and Application (
THETA
), Cairo, Egypt, Jan. 3–6, pp.
133
137
.
23.
Du
,
G.
,
Chen
,
J.
, and
Cao
,
R. J.
,
2010
, “
A Optimization Design Platform for Wind Turbine Airfoil Based on Isight
,”
Acta Energiae Sol. Sin.
,
31
(
7
), pp.
891
895
.
24.
Liu
,
K.
,
Liu
,
Y.
,
Sun
,
M.
,
Li
,
X.
, and
Wu
,
Y.
,
2016
, “
Spindle Axial Thermal Growth Modeling and Compensation on CNC Turning Machines
,”
Int. J. Adv. Manuf. Technol.
,
87
(
5
), pp.
2285
2292
.
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