Advertisement

Research on modal analysis method of CNC machine tool based on operational impact excitation

  • Bin Li
  • Liangjie Li
  • Huanbin He
  • Xinyong MaoEmail author
  • Xuchu Jiang
  • Yili Peng
ORIGINAL ARTICLE
  • 24 Downloads

Abstract

With the rapid development of modern industry and industrial upgrading, machine tool performances such as high machining speed, high machining accuracy, and high reliability have gradually become the development trend of high-end CNC machine tools. The vibration characteristics of the machine structure become an important factor affecting the machining quality and processing efficiency of the machine tool. Since the movable parts of the CNC machine tool will impact the machine structure itself during the acceleration and deceleration process, by identifying the structural vibration response signal, the modal parameters of the machine tool in the running state can be obtained, called active excitation mode analysis. However, this method still has certain defects in theory and experiment. For example, the excitation principle is not theoretically explained, and the excitation energy and the frequency band of the method are limited. To solve these problems, this paper conducts more comprehensive research on the modal analysis method of CNC machine tools based on operational impact excitation. The main research contents are as follows: considering the rigid body motion of the table and the elastic collision of the screw nut pair, the impact excitation is modeled and analyzed. We have introduced a response-based modal identification algorithm. The influence factors of impact excitation energy and frequency band were studied from both theoretical and experimental aspects. Design three excitation sequences for workbench excitation and spindle excitation, respectively, analyze the vibration response and modal identification of the machine tool structure under different excitation sequences. It is verified that the method does not depend on the specific excitation sequence, as long as it satisfies the random characteristics. Aiming at the problem of insufficient excitation energy of the machine tool structure for single-component impact excitation, a multi-component joint impact excitation method based on the principle of multi-point excitation technology is proposed. The design experiment is carried out to verify the impact excitation method, which shows that the joint excitation has better excitation effect than single-axis excitation.

Keywords

CNC machine tool Operational impact excitation Excitation sequence Multi-component joint excitation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

The authors are grateful to the other participants of the project for their cooperation.

Funding information

The research is supported by the National Natural Science Foundation of China under Grants No. 51775212 and 51625502.

References

  1. 1.
    Kwiatkowski AW, Al-Samarai HM (1968) Identification of milling machine receptances from random signals during cutting. Annals of the CIRP 16Google Scholar
  2. 2.
    Moriwaki T, Iwata K (1976) In-process analysis of machine tool structure dynamics and prediction of machining chatter. J Manuf Sci Eng 98(1):301–305Google Scholar
  3. 3.
    Kushnir E (2004) Application of operational modal analysis to a machine tool testing. In: Proceedings of 2004 ASME International Mechanical Engineering Congress and Exposition (IMECE). Anaheim, California. ASME, USAGoogle Scholar
  4. 4.
    Optiz H, Week M (1969) Determination of the transfer function by means of spectral density measurements and its application to the dynamic investigation of machine tools under machining conditions. In: Proceedings of the 10th International MTDR ConferenceGoogle Scholar
  5. 5.
    Minis IE, Magrab EB, Pandelidis IO (1990) Improved methods for the prediction of chatter in turning, part 1: determination of structural response parameters. Journal of Engineering for Industry 112(1):12–20CrossRefGoogle Scholar
  6. 6.
    Tounsi N, Otho A (2000) Identification of machine–tool–workpiece system dynamics. Int J Mach Tools Manuf 40(9):1367–1384CrossRefGoogle Scholar
  7. 7.
    Bonzanigo F, Tsudi J P. Identification of milling machine structures from the output signal only. In: Proceedings of Eurisco-83Google Scholar
  8. 8.
    Zaghbani I, Songmene V (2009) Estimation of machine-tool dynamic parameters during machining operation through operational modal analysis. Int J Mach Tools Manuf 49(12):947–957CrossRefGoogle Scholar
  9. 9.
    özşahin O, Budak E, özgüven HN (2011) Investigating dynamics of machine tool spindles under operational conditions. Advanced Materials Research 223:610–621CrossRefGoogle Scholar
  10. 10.
    Li B, Cai H, Mao X, Huang J, Luo B (2013) Estimation of CNC machine-tool dynamic parameters based on random cutting excitation through operational modal analysis. Int J Mach Tools Manuf 71:26–40CrossRefGoogle Scholar
  11. 11.
    Cai H, Mao X, Li B, Luo B (2015) Estimation of FRFs of machine tools in output-only modal analysis. Int J Adv Manuf Techno 77(1–4):117–130CrossRefGoogle Scholar
  12. 12.
    Li C (2007) Research on method of extracting modal parameters of CNC Machine tools based on response signal. Huazhong University of Science & TechnologyGoogle Scholar
  13. 13.
    Li B, Wei Y Q, Mao X Y*, Mao K M, Liu H Q, Tian H L (2010) A novel vibration exciting method for NC machine tools. International Conference on System Science 2 :45–48Google Scholar
  14. 14.
    Li B, Luo B, Mao X, Cai H, Peng F, Liu H (2013) A new approach to identifying the dynamic behavior of CNC machine tools with respect to different worktable feed speeds. Int J Mach Tools Manuf 72:73–84CrossRefGoogle Scholar
  15. 15.
    Mao X, Liu Q, Li B, Liu H, Yin L, Li J (2016) Investigation on the dynamic behavior of machine tool with respect to different worktable feed rates. Mechanical and Aerospace Engineering (ICMAE), 7th International Conference on. IEEE:253–256Google Scholar
  16. 16.
    Hung JP, Wu JS, Chiu JP (2016) Impact failure analysis of re-circulating mechanism in ball screw. Engineering Failure Analysis 11:561–573CrossRefGoogle Scholar
  17. 17.
    Braccesi C, Landi L (2007) A general elastic - plastic approach to impact analysis for stress state limit evaluation in ball screw bearings return system. International Journal of Impact Engineering 34(7):1272–1285CrossRefGoogle Scholar
  18. 18.
    Zhang Z, Song X, Jiang H et al (2008) Research on collision between ball and returner in ball screw pair. China Mechanical Engineering 19(7):850–853Google Scholar
  19. 19.
    Igarashi T, Tokunaga Y, Kamimura N (1995) Studies on the sound and vibration of a ball screw (5th Report, Sound caused by random waviness on flank surfaces). Transactions of the Japan Society of Mechanical Engineers 61(588):3369–3374CrossRefGoogle Scholar
  20. 20.
    Zhang Z, Song X, Jiang H (2008) Experimental study on axial vibration excitation factors of precision ball Screw Pair. Journal of Vibration Measurement & Diagnosis 28(1):14–17Google Scholar
  21. 21.
    Yan X (2005) Stress wave analysis of impact process. Journal of Kunming Metallurgy College 21(1):50–51Google Scholar
  22. 22.
    Feng G, Pan Y (2012) Investigation of ball screw preload variation based on dynamic modeling of a preload adjustable feed-drive system and spectrum analysis of ball-nuts sensed vibration signals. Int J Mach Tools Manuf 52(1):85–96CrossRefGoogle Scholar
  23. 23.
    Jiang D, Hong M, Zhou L (2009) Study on operational modal analysis of ship structures based on ambient excitation. Proceeding of the 16th International Congress on Sound and Vibration No.234, Krakow, PolandGoogle Scholar
  24. 24.
    Kim K (2017) A study on modal parameter estimation method based on operational modal analysis for ship structure. International Journal of Mechanical & Mechatronics Engineering 17(2):66–73Google Scholar
  25. 25.
    Zhang Y (2014) Experiment research on modal analysis of CNC machine tool for active spindle movement excitation. Wuhan: Huazhong University of Science & TechnologyGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Bin Li
    • 1
  • Liangjie Li
    • 1
  • Huanbin He
    • 1
  • Xinyong Mao
    • 1
    Email author
  • Xuchu Jiang
    • 1
  • Yili Peng
    • 1
  1. 1.National NC System Engineering Research Center, School of Mechanical Science and EngineeringHuazhong University of Science and Technology (HUST)WuhanPeople’s Republic of China

Personalised recommendations