Weitere Artikel dieser Ausgabe durch Wischen aufrufen
Supported by National Natural Science Foundation of China (Grant No. 51475343), and International Science and Technology Cooperation Program of China (Grant No. 2015DFA70340).
Thermal error monitoring technology is the key technological support to solve the thermal error problem of heavy-duty CNC (computer numerical control) machine tools. Currently, there are many review literatures introducing the thermal error research of CNC machine tools, but those mainly focus on the thermal issues in small and medium-sized CNC machine tools and seldom introduce thermal error monitoring technologies. This paper gives an overview of the research on the thermal error of CNC machine tools and emphasizes the study of thermal error of the heavy-duty CNC machine tool in three areas. These areas are the causes of thermal error of heavy-duty CNC machine tool and the issues with the temperature monitoring technology and thermal deformation monitoring technology. A new optical measurement technology called the “fiber Bragg grating (FBG) distributed sensing technology” for heavy-duty CNC machine tools is introduced in detail. This technology forms an intelligent sensing and monitoring system for heavy-duty CNC machine tools. This paper fills in the blank of this kind of review articles to guide the development of this industry field and opens up new areas of research on the heavy-duty CNC machine tool thermal error.
L Uriarte, M Zatarain, D Axinte, et al. Machine tools for large parts. CIRP Annals - Manufacturing Technology, 2013, 62(2): 731–750.
J Bryan. International status of thermal error research. CIRP Annals– Manufacturing Technology, 1990, 39(2): 645–656.
J G Yang. Present situation and prospect of error compensation technology for NC machine tool. Aeronautical Manufacturing Technology, 2012, 48(5): 40–45. (in Chinese)
C H Wu, Y T Kung. Thermal analysis for the feed drive system of a CNC machine center. International Journal of Machine Tools and Manufacture, 2003, 43(15): 1521–1528.
J H Lee, S H Yang. Statistical optimization and assessment of a thermal error model for CNC machine tools. International Journal of Machine Tools and Manufacture, 2002, 42(1): 147–155.
J S Chen, W Y Hsu, Characterizations and models for the thermal growth of a motorized high speed spindle. International Journal of Machine Tools and Manufacture, 2003, 43(11): 1163–1170.
S Yang, J Yuan, J Ni. The improvement of thermal error modeling and compensation on machine tools by CMAC neural network. International Journal of Machine Tools and Manufacture, 1996, 36(4): 527–537.
C D Mize, J C Ziegert. Neural network thermal error compensation of a machining center. Precision Engineering, 2000, 24(4): 338–346.
D S Lee, J Y Choi, D H Choi. ICA based thermal source extraction and thermal distortion compensation method for a machine tool. International Journal of Machine Tools and Manufacture, 2003, 43(6): 589–597.
H Yang, J Ni. Dynamic neural network modeling for nonlinear, nonstationary machine tool thermally induced error. International Journal of Machine Tools and Manufacture, 2005, 45(4-5): 455–465.
Y Kang, C W Chang, Y Huang, et al. Modification of a neural network utilizing hybrid filters for the compensation of thermal deformation in machine tools. International Journal of Machine Tools and Manufacture, 2007, 47(2): 376–387.
H Wu, H T Zhang, Q J Guo, et al. Thermal error optimization modeling and real-time compensation on a CNC turning center. Journal of Materials Processing Technology, 2008, 207(1-3): 172–179.
Q J Guo, J G Yang, H Wu. Application of ACO-BPN to thermal error modeling of NC machine tool. The International Journal of Advanced Manufacturing Technology, 2010, 50(5): 667–675.
Y Zhang, J G Yang, H Jiang. Machine tool thermal error modeling and prediction by grey neural network. The International Journal of Advanced Manufacturing Technology, 2012, 59(9): 1065–1072.
International Organization for Standardization Technical Committees. ISO 230-3-2007 Test code for machine tools–Part 3: Determination of thermal effects. Geneva: International Organization for Standardization, 2007.
International Organization for Standardization Technical Committees. ISO 10791-10-2007 Test conditions for machining centres–Part 10: Evaluation of thermal distortion. Geneva: International Organization for Standardization, 2007.
International Organization for Standardization Technical Committees. ISO 13041-8-2004 Test conditions for numerically controlled turning machines and turning centres - Part 8: Evaluation of thermal distortions. Geneva: International Organization for Standardization, 2004.
M Weck, P Mckeown, R Bonse, et al. Reduction and Compensation of Thermal Errors in Machine Tools. CIRP Annals - Manufacturing Technology, 1995, 44(2): 589–598.
R Ramesh, M A Mannan, A N Poo. Error compensation in machine tools - a review: Part II: thermal errors. International Journal of Machine Tools and Manufacture, 2000, 40(9): 1257–1284.
R Ramesh, M A Mannan, A N Poo. Thermal error measurement and modelling in machine tools.: Part I. Influence of varying operating conditions. International Journal of Machine Tools and Manufacture, 2003, 43(4): 391–404.
R Ramesh, M A Mannan, A N Poo, et al. Thermal error measurement and modelling in machine tools. Part II. Hybrid bayesian network-support vector machine model. International Journal of Machine Tools and Manufacture, 2003, 43(4): 405–419.
J W Li, W J Zhang, G S Yang, et al. Thermal-error modeling for complex physical systems: the-state-of-arts review. The international Journal of Advanced Manufacturing Technology, 2009, 42(1): 168–179.
J Z Fu, X Y Yao, Y He, et al. Development of thermal error compensation technology for NC machine tool. Aeronautical Manufacturing Technology, 2010 (4): 64–66. (in Chinese)
J Mayr, J Jedrzejewski, E Uhlmann, et al. Thermal issues in machine tools. CIRP Annals - Manufacturing Technology, 2012, 61(2): 771–791.
Y Li, W H Zhao, S H Lan, et al. A review on spindle thermal error compensation in machine Tools. International Journal of Machine Tools and Manufacture, 2015, 95: 20–38.
H T Wang, T M Li, L P Wang, et al. Review on thermal error modeling of machine tools. Journal of Mechanical Engineering, 2015, 51(9): 119–128. (in Chinese)
A Palmgren, B Ruley. Ball and roller bearing engineering. Philadelphia: SKF Industries, Inc.,1945.
T A Harris. Rolling bearing analysis. 4th edition. New York: Wiley, 2001.
Z Q Liu, Y H Zhang, H Su. Thermal analysis of high speed rolling bearing. Lubrication and Sealing, 1998, 4: 66–68. (in Chineses)
J L Stein, J F Tu. A State-space model for monitoring thermally induced preload in anti-friction spindle bearings of high-speed machine tools. Journal of Dynamic Systems Measurement and Control, 1994, 116(3): 372–386.
J H Rumbarger, E G Filetti, D Gubernick, et al. Gas turbine engine main shaft roller bearing system analysis. Journal of Lubrication Technology, 1973, 95(4): 401–416.
G C Chen, L Q Wang, L Gu, et al. Heating analysis of the high speed ball bearing, Journal of Aerospace Power, 2007, 22(1): 163–168. (in Chinese)
R S Moorthy, V P Raja. An improved analytical model for prediction of heat generation in angular contact ball bearing. Arabian Journal for Science and Engineering, 2014, 39(11): 8111–8119.
W M Hannon. Rolling-element bearing heat transfer - part I.: Analytic model. Journal of Tribology, 2015, 137(3): 031102.
F P Incroper, D P Dewitt, T L Bergman, et al. Fundamentals of heat and mass transfer. 6th ed. Beijing: Chemical Industry Press, 2011. (in Chinese)
B Bossmanns, J F Tu. A thermal model for high speed motorized spindles. International Journal of Machine Tools and Manufacture, 1999, 39(9): 1345–1366.
B Bossmanns, J F Tu. A power flow model for high speed motorized spindles - heat generation characterization. Journal of Manufacturing Science and Engineering, 2001,123(3): 494–505.
T Holkup, H Cao, P Kolář, et al. Thermo-mechanical model of spindles. CIRP Annals - Manufacturing Technology, 2010, 59(1): 365–368.
J Takabi, M M Khonsari. Experimental testing and thermal analysis of ball bearings. Tribology International, 2013, 60(7): 93–103.
J Jędrzejewski, Z Kowal, W Kwaśny, et al. High-speed precise machine tools spindle units improving. Journal of Materials Processing Technology, 2005, 162-163: 615–621.
K S Kim, D W Lee, S M Lee, et al. A numerical approach to determine the frictional torque and temperature of an angular contact ball bearing in a spindle system. International Journal of Precision Engineering and Manufacturing, 2015, 16(1): 135–142.
Z C Du, S Y Yao, J G Yang. Thermal behavior analysis and thermal error compensation for motorized spindle of machine tools. International Journal of Precision Engineering and Manufacturing, 2015, 16(7): 1571–1581.
J Y Xia, B Wu, Y M Hu, et al. Experimental research on factors influencing thermal dynamics characteristics of feed system. Precision Engineering, 2010, 34(2): 357–368.
Z Z Xu, X J Liu, C H Choi, et al. A study on improvement of ball screw system positioning error with liquid-cooling. International Journal of Precision Engineering and Manufacturing, 2012, 13(12): 2173–2181.
W S Yun, S K Kim, D W Cho. Thermal error analysis for a CNC lathe feed drive system. International Journal of Machine Tools and Manufacture, 1999, 39(7): 1087–1101
J Mayr, M Ess, S Weikert, et al. Thermal behaviour improvement of linear axis . Proceedings of 11th euspen International Conference, Como, Italy, May 23-26, 2011: 291–294.
Z Z Xu, X J Liu, S K Lyu. Study on positioning accuracy of nut/shaft air cooling ball screw for high-precision feed drive. International Journal of Precision Engineering and Manufacturing, 2014, 15(1): 123–128.
S K Kim, D W Cho. Real-time estimation of temperature distribution in a ball-screw system. International Journal of Machine Tools and Manufacture, 1997, 37(4): 451–464.
M F Zaeh, T Oertli, J Milberg. Finite element modelling of ball screw feed drive systems. CIRP Annals - Manufacturing Technology, 2004, 53(2): 289–292.
C Jin, B Wu, Y M Hu. Heat generation modeling of ball bearing based on internal load distribution. Tribology International, 2012, 45(1): 8–15.
C Jin, B Wu, Y M Hu, et al. Temperature distribution and thermal error prediction of a CNC feed system under varying operating conditions. Precision Engineering, 2015, 77(9–12): 1979–1992.
C Jin, B Wu, Y M Hu, et al. Thermal characteristics of a CNC feed system under varying operating conditions. Precision Engineering, 2015, 42(9-12): 151–164.
B Tan, X Y Mao, H Q Liu, et al. A thermal error model for large machine tools that considers environmental thermal hysteresis effects. International Journal of Machine Tools and Manufacture, 2014. 82-83(7): 11–20.
C X Zhang, F Gao, Y Li. Thermal error characteristic analysis and modeling for machine tools due to time-varying environmental temperature. Precision Engineering, 2017, 47: 231–238.
N S Mian, S Fletcher, A P Longstaff, et al. Efficient thermal error prediction in a machine tool using finite element analysis. Measurement Science and Technology, 2011, 22(8): 085107.
N S Mian, S Fletcher, A P Longstaff, et al. Efficient estimation by FEA of machine tool distortion due to environmental temperature perturbations. Precision Engineering, 2013, 37(2): 372–379.
J F Zhang, P F Feng, CHEN C, et al. A method for thermal performance modeling and simulation of machine tools. The International Journal of Advanced Manufacturing Technology, 2013, 68(5): 1517–1527.
J Mayr, S Weikert, Wegener K, et al. Comparing the thermo-mechanical-behaviour of machine tool frame designs using a FDM-FEA simulation approach . Proceedings of the 22nd Annual ASPE Meeting, Dallas, TX, United states, October 14-19, 2007: 17–20.
J Mayr, M Ess, S Weikert, et al. Calculating thermal location and component errors on machine tools . Proceedings of the 24nd Annual ASPE Meeting, Monterey, CA, United states, October 4-9, 2009.
J Mayr, M Ess, S Weikert, et al. Compensation of thermal effects on machine tools using a FDEM simulation approach // 9th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, Uxbridge, United kingdom, June 30-July 2, 2009: 38–47.
F L M Delbressine, G H J Florussen, L A Schijvenaars, et al. Modelling thermomechanical behaviour of multi-axis machine tools. Precision Engineering, 2006, 30(1): 47–53.
J Yang, X S Mei, B Feng, et al. Experiments and simulation of thermal behaviors of the dual-drive servo feed system. Chinese Journal of Mechanical Engineering, 2015, 28(1): 76–87.
C Jin, B Wu, Y M Hu. Wavelet neural network based on NARMA-L2 model for prediction of thermal characteristics in a feed system. Chinese Journal of Mechanical Engineering, 2011, 24(1): 33–41.
J Zhu, J Ni, A J Shih. Robust machine tool thermal error modeling through thermal mode concept. Journal of Manufacturing Science and Engineering, 2008, 130(6): 061006.
F C Li, H T Wang, T M Li. Research on thermal error modeling and prediction of heavy CNC machine tools. Journal of Mechanical Engineering, 2016, 52(11): 154–160. (in Chinese)
C Chen, J F Zhang, Z J Wu, et al. A real-time measurement method of temperature fields and thermal errors in machine tools // Proceeding of the 2010 International Conference on Digital Manufacturing and Automation, Changsha, China. 2010, 1: 100–103.
O Horejš, M Mareš, L Novotný, et al. Advanced modeling of thermally induced displacements and its implementation into standard CNC controller of horizontal milling center. Procedia CIRP, 2012, 4: 67–72.
J Vyroubal. Compensation of machine tool thermal deformation in spindle axis direction based on decomposition method. Precision Engineering, 2012, 36 (1): 121–127.
H J Pahk, S W Lee. Thermal error measurement and real time compensation system for the CNC machine tools incorporating the spindle thermal error and the feed axis thermal error. The International Journal of Advanced Manufacturing Technology, 2002, 20(7): 487–494.
H Yang, J Ni. Dynamic modeling for machine tool thermal error compensation. Journal of Manufacturing Science and Engineering, 2003, 125(2): 245–254.
D Werschmoeller, X C Li. Measurement of tool internal temperatures in the tool - chip contact region by embedded micro thin film thermocouples. Journal of Manufacturing Processes, 2011, 13(2): 147–152.
J Liu, G Chen, C H Ji, et al. An investigation of workpiece temperature variation of helical milling for carbon fiber reinforced plastics (CFRP). International Journal of Machine Tools and Manufacture, 2014, 86(11):89–103.
J Qiu, C S Liu, Q W Liu, et al. Thermal errors of planer type NC machine tools and its improvement measures. Journal of Mechanical Engineering, 2012,48(21): 149–157. (in Chinese)
C W Wu, C H Tang, C F Chang, et al. Thermal error compensation method for machine center. International Journal of Advanced Manufacturing Technology, 2012, 59(5): 681–689.
E Uhlmann, J Hu. Thermal modelling of a high speed motor spindle. Procedia Cirp, 2012, 1: 313–318.
T Zhang, W H Ye, R J Liang, et al. Study on thermal behavior analysis of nut/shaft air cooling ball screw for high-precision feed drive. Chinese Journal of Mechanical Engineering, 2013, 26(1): 158–165.
American National Standards Institute. ANSI/ASME B5.54-2005 Methods for Performance Evaluation of Computer Numerically Controlled Machining Centers. Washington: American National Standards Institute, 2005.
H Schwenke, W Knapp, H Haitjema, et al. Geometric error measurement and compensation of machines: an update. CIRP Annals - Manufacturing Technology, 2008, 57(2): 660–675.
A R J Ruiz, J G Rosas, F S Granja, et al. A real-time tool positioning sensor for machine-tools. Sensors, 2009, 9(10): 7622–7647.
E Gomez-Acedo, A Olarra, L N L D L Calle. A method for thermal characterization and modeling of large gantry-type machine tools. The International Journal of Advanced Manufacturing Technology, 2012, 62(9): 875–886.
S K Lee, J H Yoo, M S Yang. Effect of thermal deformation on machine tool slide guide motion. Tribology International, 2003, 36(1): 41–47.
Z D Zhou, Y G Tan, M Y Liu, et al. Actualities and development on dynamic monitoring and diagnosis with distributed fiber Bragg Grating in mechanical systems. Journal of Mechanical Engineering, 2013, 49(19): 55–69. (in Chinese)
H N Li, L Ren. Structural health monitoring based on fiber grating sensing technology. Beijing: China Building Industry Press, 2008. (in Chinese)
N Hirayama, Y Sano. Fiber Bragg grating temperature sensor for practical use. ISA Trans, 2000, 39(2): 169–173.
D G Kim, H C Kang, J K Pan, et al. Sensitivity enhancement of a fiber Bragg grating temperature sensor combined with a bimetallic strip. Microwave and Optical Technology Letters, 2014, 56(8): 1926–1929.
Y G Zhan. Study on high resolution optical fiber grating temperature sensor research. Chinese Journal of Lasers, 2005, 32(1): 83–86. (in Chinese)
W He, X D Xu, D S Jiang. High-sensitivity fiber Bragg grating temperature sensor with polymer jacket and its low-temperature characteristic. Acta Optica Sinica, 2004, 24(10): 1316–1319. (in Chinese)
C H Lee, M K Kim, K T Kim, et al. Enhanced temperature sensitivity of fiber Bragg grating temperature sensor using thermal expansion of copper tube. Microwave and Optical Technology Letters, 2011, 53(7): 1669–1671.
C Lupi, F Felli, A Brotzu, et al. Improving FBG sensor sensitivity at cryogenic temperature by metal coating. IEEE Sensors Journal, 2008, 8(7): 1299–1304.
Y L Li, H Zhang, Y Feng, et al. Metal coating of fiber Bragg grating and the temperature sensing character after metallization. Optical Fiber Technology, 2009, 15(4): 391–397.
Y Feng, H Zhang, Y L Li, et al. Temperature sensing of metal-coated fiber Bragg grating. IEEE/ASME Transactions on Mechatronics, 2010, 15(4): 511–519.
R S Shen, J Zhang, Y Wang, et al. Study on high-temperature and high-pressure measurement by using metal-coated FBG. Microwave and Optical Technology Letters, 2008, 50(5): 1138–1140.
M J Guo, D S Jiang. Low temperature properties of fiber Bragg grating temperature sensor with plating gold. Chinese Journal of Low Temperature Physics, 2006, 28(2): 138–141. (in Chinese)
Y G Zhan, S L Xue, Q Y Yang, et al. A novel fiber Bragg grating high-temperature sensor. Optik - International Journal for Light and Electron Optics, 2008, 119(11): 535–539.
Y Liu, Z D Zhou, E L Zhang, et al. Measurement error of surface-mounted fiber Bragg grating temperature sensor. Review of Scientific Instruments, 2014, 85(6): 064905.
Y Liu, J Zhang. Model Study of the Influence of ambient temperature and installation types on surface temperature measurement by using a fiber Bragg grating sensor. Sensors, 2016, 16(7): 975.
M Y Liu, E L Zhang, Z D Zhou, et al. Measurement of temperature field for the spindle of machine tool based on optical fiber Bragg grating sensors. Advances in Mechanical Engineering, 2013, 2: 940626.
Y F Dong, Z D Zhou, Z C Liu, et al. Temperature field measurement of spindle ball bearing under radial force based on fiber Bragg grating sensors. Advances in Mechanical Engineering, 2015, 7(12): 1–6.
J Huang, Z D Zhou, M Y Liu, et al. Real-time measurement of temperature field in heavy-duty machine tools using fiber Bragg grating sensors and analysis of thermal shift errors. Mechatronics, 2015, 31: 16–21.
N S Kim, N S Cho. Estimating deflection of a simple beam model using fiber optic bragg-grating sensors. Experimental Mechanics, 2004, 44(4): 433–439.
S J Chang, N S Kim. Estimation of displacement response from FBG strain sensors using empirical mode decomposition technique. Experimental Mechanics, 2012, 52(6): 573–589.
L H Kang, D K Kim, J H Han, Estimation of dynamic structural displacements using fiber Bragg grating strain sensors. Journal of Sound and Vibration, 2007, 305(3): 534–542.
D Kang, W Chung. Integrated monitoring scheme for a maglev guideway using multiplexed FBG sensor arrays. NDT & E International, 2009, 42(4): 260–266.
J C Yi, X J Zhu, H S Zhang, et al. Spatial shape reconstruction using orthogonal fiber Bragg grating sensor array. Mechatronics, 2012, 22(6): 679–687.
P Bosetti, S Bruschi. Enhancing positioning accuracy of CNC machine tools by means of direct measurement of deformation. The International Journal of Advanced Manufacturing Technology, 2012, 58(5-8): 651–662.
F Biral, P Bosetti, R Oboe, et al. A new direct deformation sensor for active compensation of positioning errors in large milling machines .9th IEEE International Workshop on Advanced Motion Control, Istanbul, Turkey, March 27-29, 2006: 126–131.
F Biral, P Bosetti. On-line measurement and compensation of geometrical errors for Cartesian numerical control machines . 9th IEEE International Workshop on Advanced Motion Control, Istanbul, Turkey, March 27-29, 2006: 120–125.
Y Liu, M Y Liu, C X Yi, et al. Measurement of the deformation field for machine tool based on optical fiber Bragg grating sensors . 2014 International Conference on Innovative Design and Manufacturing, Quebec, Canada, August 13-15, 2014: 222–226.
R Y Li, Y G Tan, Y Liu, et al. A new deformation measurement method for heavy-duty machine tool base by multipoint distributed FBG sensors . Applied Optics and Photonics, China: Optical Fiber Sensors and Applications (AOPC 2015), Beijing, China, May 5-7, 2015: 967903.
R Y Li, Y G Tan, L Hong, et al. A temperature-independent force transducer using one optical fiber with multiple Bragg gratings. IEICE Electronic Express, 2016, 13(10): 20160198.
Y Li, Q Liu, R Tong, et al. Shared and service-oriented CNC machining system for intelligent manufacturing process. Chinese Journal of Mechanical Engineering, 2015, 28(6): 1100–1108.
R Harrison, D Vera, B Ahmad. Engineering the smart factory. Chinese Journal of Mechanical Engineering, 2016, 29(6): 1046–1051.
- Actualities and Development of Heavy-Duty CNC Machine Tool Thermal Error Monitoring Technology
- Chinese Mechanical Engineering Society
in-adhesives, MKVS, Zühlke/© Zühlke, Nordson/© Nordson, ViscoTec/© ViscoTec, Hellmich GmbH/© Hellmich GmbH