Skip to main content
Log in

Research on double-rotor dynamic grinding model and simulation algorithm for crankshaft main journal

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Crankshaft is a core part of automobile engine to bear impact load and transmit power. Precision grinding is the most important machining method to achieve high precision of crankshaft main journal. Although many scholars have established various simulation models in the field of cylindrical grinding, it is difficult to carry out effective quantitative simulation for a given crankshaft main journal grinding system. Aiming at the shortcomings of the existing models, a double-rotor dynamic model is proposed, which considers the interaction between the grinding wheel and the main journal, and iterative algorithm is adopted to simulate material removal and roundness change in the grinding process of the main journal. The normal force between grinding wheel and the main journal is defined in detail in the algorithm, which is closer to the actual grinding process. For a given crankshaft grinding system, different grinding strategies of the main journal are quantitatively simulated by using the model. The proposed model and algorithm are validated by experiments, which can provide a basic model for the further study of the crankshaft cylindrical grinding system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Not applicable.

References

  1. Jianhua W (2012) Automobile engine theory. National Defense Industry Press, Beijing

    Google Scholar 

  2. Liqiang D, Xueping Z, Zhenqiang Y (2013) A method to control the deformation of main journals in grinding process. Mach Des Res 29(3):66–69. https://doi.org/10.13952/j.cnki.jofmdr.2013.03.005

    Article  Google Scholar 

  3. Yucan F, Lin T, Jiuhua X (2015) Development and application on the grinding process modeling and simulation. J Mech Eng 51(7):197–205. https://doi.org/10.3901/JME.2015.07.197

    Article  Google Scholar 

  4. Rudrapati R, Pal PK, Bandyopadhyay A (2016) Modeling and optimization of machining parameters in cylindrical grinding process. Int J Adv Manuf Technol 82(9-12):2167–2182. https://doi.org/10.1007/s00170-015-7500-9

    Article  Google Scholar 

  5. Fricker DC, Speight A, Pearce TRA (2006) The modelling of roundness in cylindrical plunge grinding to incorporate wave shift and external vibration effects. Proc Inst Mech Eng B J Eng Manuf 220(8):137–1358. https://doi.org/10.1243/09544054JEM509

    Article  Google Scholar 

  6. Pearce TRA, Fricker DC, Speight A (2007) Indirect measurement of grinding wheel run-out using acoustic emission. Int J Manuf Technol Manag 33(12):139–154. https://doi.org/10.1504/IJMTM.2007.014147

    Article  Google Scholar 

  7. Pearce TRA, Flicker DC, Speight A (2007) The effect on workpiece roundness of the run-out of CBN electroplated grinding wheels. Key Eng Mater 329:483–488. https://doi.org/10.4028/www.scientific.net/KEM.329.483

    Article  Google Scholar 

  8. Weck M, Alldieck J (1989) The originating mechanisms of wheel regenerative grinding vibration. CIRP Ann Manuf Technol 38(1):381–384. https://doi.org/10.1016/S0007-8506(07)62728-0

    Article  Google Scholar 

  9. Wang LP, Wang D, Wang B (2019) An analysis method of oscillating grinding motion model for crankshaft pin journal. IEEE Access 7:137163–137171. https://doi.org/10.1109/ACCESS.2019.2942080

    Article  Google Scholar 

  10. Chiu N, Malkin S (1993) Computer simulation for cylindrical plunge grinding. Ann Manuf Technol 42(1):383–387. https://doi.org/10.1016/s0007-8506(07)62467-6

    Article  Google Scholar 

  11. Saglam H, Unsacar F, Yaldiz S (2005) An experimental investigation as to the effect of cutting parameters on roundness error and surface roughness in cylindrical grinding. Int J Prod Res 43(11):2309–2322. https://doi.org/10.1080/00207540412331330110

    Article  Google Scholar 

  12. Saglam H, Yaldiz S, Unsacar F (2007) The effect of tool geometry and cutting speed on main cutting force and tool tip temperature. Mater Des 191(28):101–111. https://doi.org/10.1016/j.matdes.2005.05.015

    Article  Google Scholar 

  13. Leonesio M, Parenti P, Cassinari A, Bianchi G, Monno M (2012) A time-domain surface grinding model for dynamic simulation. Procedia CIRP 4(1):166–171. https://doi.org/10.1016/j.procir.2012.10.030

    Article  Google Scholar 

  14. Yang Y, Lin J, Xu S (2012) Surface grinding machine stability characteristics limited prediction. Mech Eng Res 2(2). https://doi.org/10.5539/mer.v2n2p114

  15. Cui Q, Ding H, Cheng K (2015) An analytical investigation on the workpiece roundness generation and its perfection strategies in centerless grinding. Proc Inst Mech Eng B J Eng Manuf 229(3):513–518. https://doi.org/10.1177/0954405414530899

    Article  Google Scholar 

  16. Jinglong S, Fei Q, Pei C, Tong A (2016) A predictive model of grinding force in silicon wafer self-rotating grinding. Int J Mach Tools Manuf 109:74–86. https://doi.org/10.1016/j.ijmachtools.2016.07.009

    Article  Google Scholar 

  17. Li B, Dai C, Ding W, Yang C, Shumyacher V (2020) Prediction on grinding force during grinding powder metallurgy nickel-based superalloy fgh96 with electroplated CBN abrasive wheel. Chin J Aeronaut. https://doi.org/10.1016/j.cja.2020.05.002

  18. Xi X, Ding W, Wu Z, Anggei L (2020) Performance evaluation of creep feed grinding of γ-TiAl intermetallics with electroplated diamond wheels. Chin J Aeronaut. https://doi.org/10.1016/j.cja.2020.04.031

  19. Azizi A, Mohamadyari M (2015) Modeling and analysis of grinding forces based on the single grit scratch. Int J Adv Manuf Technol 78(5-8):1223–1231. https://doi.org/10.1007/s00170-014-6729-z

    Article  Google Scholar 

  20. Jiang J, Ge P, Sun S, Wang D, Wang Y, Yang Y (2016) (2016) From the microscopic interaction mechanism to the grinding temperature field: an integrated modelling on the grinding process. Int J Mach Tool Manu 110:27–42. https://doi.org/10.1016/j.ijmachtools.2016.08.004

    Article  Google Scholar 

  21. Zhu W, Yang Y, Li HN, Axinte D, Beaucamp A (2019) Theoretical and experimental investigation of material removal mechanism in compliant shape adaptive grinding process. Int J Mach Tools Manuf 142:76–97. https://doi.org/10.1016/j.ijmachtools.2019.04.011

    Article  Google Scholar 

  22. Wanli X, Wenxiang D, Jianhua C, Lianggang Z, Wenbiao S (2020) A novel double rotor coupling model for inner bore grinding process. Int J Adv Manuf Technol 106(7-8):3357–3366. https://doi.org/10.1007/s00170-019-04873-x

    Article  Google Scholar 

  23. Wanli X, Jianhua C, Wenxiang D, Xu Z (2019) Dual-rotor coupling model and simulation algorithm for round journal grinding process. J Mech Eng 55(11):170–177. https://doi.org/10.3901/JME.2019.21.170

    Article  Google Scholar 

  24. Wenbo B, Quan B, Haiyan L (2015) Fundamentals of vibration mechanics and Matlab Application. Tsinghua University Press, Beijing

    Google Scholar 

  25. Shengyi L, Yifan D (2007) In-position detection and error separation technology for precision and ultra-precision machining. National University of Defense Technology Press, Changsha

    Google Scholar 

  26. Jin L, Yan Z, Xie L, Gou W, Tang L (2014) An experimental investigation of spindle rotary error on high-speed machining center. Int J Adv Manuf Technol 70(1-4):327–334. https://doi.org/10.1007/s00170-013-5270-9

    Article  Google Scholar 

  27. Anandan KP, Ozdoganlar OB (2013) An LDV-based methodology for measuring axial and radial error motions when using miniature ultra-high-speed (UHS) micromachining spindles. Precis Eng 37(1):172–186. https://doi.org/10.1016/j.precisioneng.2012.08.001

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the financial support of the National Natural Science Foundation of China (No.51575173) and the Science and Technology Major Project-Advanced NC Machine Tools & Basic Manufacturing Equipment (No: 2016ZX04003001).

Funding

This work was financially supported by the National Natural Science Foundation of China (No.51575173) and the Science and Technology Major Project-Advanced NC Machine Tools&Basic Manufacturing Equipments (No: 2016ZX04003001).

Author information

Authors and Affiliations

Authors

Contributions

Xu Zeng performed the experiments, made the simulation, and wrote the manuscript, while Wanli Xiong contributed to the conception of the study and helped perform the analysis with constructive discussions, Wenbiao Sun helped perform the analysis with constructive discussions, and Hongyan Ye and Zhiyong Tang helped perform the experiments.

Corresponding author

Correspondence to Wanli Xiong.

Ethics declarations

Ethical approval

There was no ethical issue in this project.

Consent to participate

There were no participants in this project.

Consent to publish

The authors are the owner of the data in this project and have consent to publish.

Competing interest

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zeng, X., Xiong, W., Sun, W. et al. Research on double-rotor dynamic grinding model and simulation algorithm for crankshaft main journal. Int J Adv Manuf Technol 114, 3391–3400 (2021). https://doi.org/10.1007/s00170-021-06761-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-021-06761-9

Keywords

Navigation