Skip to main content
Log in

Nonlinear vibration and super-harmonic resonance analysis of aluminum alloy friction stir welding

  • Research
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

Friction stir welding of aluminum alloy offers excellent joint quality, less residual stress and deformation, and high production efficiency when compared to conventional welding techniques. It is possible to optimize the welding process and raise the quality and efficiency of the welds by researching their nonlinear dynamic properties. In this study, a nonlinear dynamic model of friction stir welding of aluminum alloy was constructed by taking into account the flow of thermoplastic materials, time-varying upsetting force, and plastic metal friction model. The nonlinear behavior of the system was described by using bifurcation diagrams, Lyapunov exponent, time domain, fast Fourier transform (FFT) spectrum, phase plot and Poincare map. Moreover, the superharmonic resonance characteristics of the system were investigated using a multi-scale methodology, and the impact of displacement delay, displacement control, speed control, and system damping on the aluminum alloy friction stir welding system's oscillation mode were examined. According to the findings, the friction stir welding system of aluminum alloy possesses complex non-linear properties with the change of stirring pin rotation speed, feed speed and support stiffness. Furthermore, by choosing the right time delay parameters and boosting the damping, the system's stability can be enhanced.

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
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31
Fig. 32
Fig. 33
Fig. 34
Fig. 35
Fig. 36
Fig. 37

Similar content being viewed by others

Data availability

Data will be made available on request.

References

  1. Mishra, R.S., Ma, Z.Y.: Friction stir welding and processing[J]. Mater. Sci. Eng. R. Rep. 50(1–2), 1–78 (2005). https://doi.org/10.1016/j.mser.2005.07.001

    Article  Google Scholar 

  2. Threadgill, P.L., Leonard, A.J., Shercliff, H.R., et al.: Friction stir welding of aluminium alloys[J]. Int. Mater. Rev. 54(2), 49–93 (2009). https://doi.org/10.1179/174328009X411136

    Article  Google Scholar 

  3. Meng, X., Huang, Y., Cao, J., et al.: Recent progress on control strategies for inherent issues in friction stir welding[J]. Prog. Mater Sci. 115, 100706 (2021). https://doi.org/10.1016/j.pmatsci.2020.100706

    Article  Google Scholar 

  4. Wang, G., Zhao, Y., Hao, Y.: Friction stir welding of high-strength aerospace aluminum alloy and application in rocket tank manufacturing[J]. J. Mater. Sci. Technol. 34(1), 73–91 (2018). https://doi.org/10.1016/j.jmst.2017.11.041

    Article  Google Scholar 

  5. Guan, W., Zhao, Y., Liu, Y., et al.: Force data-driven machine learning for defects in friction stir welding[J]. Scripta Mater. 217, 114765 (2022). https://doi.org/10.1016/j.scriptamat.2022.114765

    Article  Google Scholar 

  6. Guan, W., Cui, L., Liang, H., et al.: The response of force characteristic to weld-forming process in friction stir welding assisted by machine learning[J]. Int. J. Mech. Sci. 253, 108409 (2023). https://doi.org/10.1016/j.ijmecsci.2023.108409

    Article  Google Scholar 

  7. Boccarusso, L., Astarita, A., Carlone, P., et al.: Dissimilar friction stir lap welding of AA 6082-Mg AZ31: Force analysis and microstructure evolution[J]. J. Manuf. Process. 44, 376–388 (2019). https://doi.org/10.1016/j.jmapro.2019.06.022

    Article  Google Scholar 

  8. Chen, G., Ma, Q., Zhang, S., et al.: Computational fluid dynamics simulation of friction stir welding: a comparative study on different frictional boundary conditions[J]. J. Mater. Sci. Technol. 34(1), 128–134 (2018). https://doi.org/10.1016/j.jmst.2017.10.015

    Article  Google Scholar 

  9. Shi, L., Chen, J., Yang, C., et al.: Thermal-fluid-structure coupling analysis of void defect in friction stir welding[J]. Int. J. Mech. Sci. 241, 107969 (2023). https://doi.org/10.1016/j.ijmecsci.2022.107969

    Article  Google Scholar 

  10. Chu, Q., Li, W.Y., Wu, D., et al.: In-depth understanding of material flow behavior and refinement mechanism during bobbin tool friction stir welding[J]. Int. J. Mach. Tools Manuf 171, 103816 (2021). https://doi.org/10.1016/j.ijmachtools.2021.103816

    Article  Google Scholar 

  11. Tongne, A., Desrayaud, C., Jahazi, M., et al.: On material flow in friction stir welded Al alloys[J]. J. Mater. Process. Technol. 239, 284–296 (2017). https://doi.org/10.1016/j.jmatprotec.2016.08.030

    Article  Google Scholar 

  12. Wang, H., Qin, G., Li, C.: Effect of different friction coefficient models on numerical simulation of inertia friction welding of 2219 Al alloy to 304 stainless steel[J]. J. Market. Res. 27, 6474–6483 (2023). https://doi.org/10.1016/j.jmrt.2023.11.079

    Article  Google Scholar 

  13. Liu, Q., Li, W., Zhu, L., et al.: Temperature-dependent friction coefficient and its effect on modeling friction stir welding for aluminum alloys[J]. J. Manuf. Process. 84, 1054–1063 (2022). https://doi.org/10.1016/j.jmapro.2022.10.068

    Article  Google Scholar 

  14. Abbasi, M., Bagheri, B., Ketabchi, M., et al.: Application of response surface methodology to drive GTN model parameters and determine the FLD of tailor welded blank[J]. Comput. Mater. Sci. 53(1), 368–376 (2012). https://doi.org/10.1016/j.commatsci.2011.08.020

    Article  Google Scholar 

  15. Abbasi, M., Hamzeloo, S.R., Ketabchi, M., et al.: Analytical method for prediction of weld line movement during stretch forming of tailor-welded blanks[J]. The International Journal of Advanced Manufacturing Technology 73, 999–1009 (2014). https://doi.org/10.1007/s00170-014-5850-3

    Article  Google Scholar 

  16. Bagheri, B., Abbasi, M., Dadaei, M.: Effect of water cooling and vibration on the performances of friction-stir-welded AA5083 aluminum joints[J]. Metallography, Microstructure, and Analysis 9, 33–46 (2020). https://doi.org/10.1007/s13632-019-00606-4

    Article  Google Scholar 

  17. Abbasi, M., Givi, M., Bagheri, B.: New method to enhance the mechanical characteristics of Al-5052 alloy weldment produced by tungsten inert gas[J]. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. (2020). https://doi.org/10.1177/0954405420929777

    Article  Google Scholar 

  18. Bagheri, B., Abbasi, M., Dadaei, M.: Mechanical behavior and microstructure of AA6061-T6 joints made by friction stir vibration welding[J]. J. Mater. Eng. Perform. 29, 1165–1175 (2020). https://doi.org/10.1007/s11665-020-04639-7

    Article  Google Scholar 

  19. Yan, Y., Xu, J., Wiercigroch, M.: Modelling of regenerative and frictional cutting dynamics[J]. Int. J. Mech. Sci. 156, 86–93 (2019). https://doi.org/10.1016/j.ijmecsci.2019.03.032

    Article  Google Scholar 

  20. Yan, Y., Liu, G., Wiercigroch, M., et al.: Safety estimation for a new model of regenerative and frictional cutting dynamics[J]. Int. J. Mech. Sci. 201, 106468 (2021). https://doi.org/10.1016/j.ijmecsci.2021.106468

    Article  Google Scholar 

  21. Chanda, A., Dwivedy, S.K.: Nonlinear dynamic analysis of flexible workpiece and tool in turning operation with delay and internal resonance[J]. J. Sound Vib. 434, 358–378 (2018). https://doi.org/10.1016/j.jsv.2018.05.43

    Article  Google Scholar 

  22. Chen, W., Yang, Z.: Identifying and evaluating spindle tool-tip dynamic response under different workloads[J]. Mech. Syst. Signal Process. 185, 109728 (2023). https://doi.org/10.1016/j.ymssp.2022.109728

    Article  Google Scholar 

  23. Zheng, F., Han, X., Lin, H., et al.: Research on the cutting dynamics for face-milling of spiral bevel gears[J]. Mech. Syst. Signal Process. 153, 107488 (2021). https://doi.org/10.1016/j.ymssp.2020.107488

    Article  Google Scholar 

  24. Huang, K., Yu, J., Luo, H., et al.: An efficient vectorization solution to cutting dynamics modeling for face-hobbing of hypoid gears[J]. Mech. Mach. Theory 191, 105504 (2024). https://doi.org/10.1016/j.mechmachtheory.203.105504

    Article  Google Scholar 

  25. Shuai, M., Yingxin, Z., Yuling, S., et al.: Nonlinear vibration and primary resonance analysis of non-orthogonal face gear-rotor-bearing system[J]. Nonlinear Dyn. 108(4), 3367–3389 (2022). https://doi.org/10.1007/s11071-022-07432-4

    Article  Google Scholar 

  26. Mo, S., Liu, Y., Huang, X., et al.: Nonlinear vibration and superharmonic resonance analysis of wind power planetary gear system[J]. Nonlinear Dyn. (2024). https://doi.org/10.1007/s11071-023-09268-y

    Article  Google Scholar 

  27. Mo, S., Wang, L., Hu, Q., et al.: Coupling failure dynamics of tooth surface morphology and wear based on fractal theory[J]. Nonlinear Dyn. 112(1), 175–195 (2024). https://doi.org/10.1007/s11071-023-09038-w

    Article  Google Scholar 

  28. Mo, S., Zhang, Y., Luo, B., et al.: The global behavior evolution of non-orthogonal face gear-bearing transmission system[J]. Mech. Mach. Theory 175, 104969 (2022)

    Article  Google Scholar 

  29. Mo, S., Zhang, Y., Chen, K., et al.: Dynamics analysis of helical gear considering de-meshing and reverse impact with EHL lubrication condition[J]. Chaos 34, 023103 (2024). https://doi.org/10.1063/5.0186433

    Article  MathSciNet  Google Scholar 

  30. Goicoechea, H.E., Lima, R., Buezas, F.S., et al.: A comprehensive Cosserat rod drill-string model for arbitrary well geometry that includes the dynamics of the cutting and lateral contact[J]. J. Sound Vib. 571, 118035 (2024). https://doi.org/10.1016/j.jsv.2023.118035

    Article  Google Scholar 

  31. Peng, X., Zhou, J.: Optimization design for dynamic characteristics of face gear drive with surface-active modification[J]. Mech. Mach. Theory 176, 105007 (2022)

    Article  Google Scholar 

  32. Shi, Z., Li, S.: Nonlinear dynamics of hypoid gear with coupled dynamic mesh stiffness[J]. Mech. Mach. Theory 168, 104589 (2022). https://doi.org/10.1016/j.mechmachtheory.2021.104589

    Article  Google Scholar 

  33. Cui, G., Li, B., Tian, W., et al.: Dynamic modeling and vibration prediction of an industrial robot in manufacturing[J]. Appl. Math. Model. 105, 114–136 (2022). https://doi.org/10.1016/j.apm.2021.12.031

    Article  MathSciNet  Google Scholar 

  34. Gebhard P.: Dynamisches verhalten von werkzeugmaschinen bei anwendung für das rührreibschweißen[M]. Herbert Utz Verlag (2011)

  35. Neumaier T.: Zur optimierung der verfahrensauswahl von kalt-, halbwarm-und warmmassivumformverfahren[M]. VDI-Verlag, (2003)

  36. Abbasi, M., Abdollahzadeh, A., Bagheri, B., et al.: Study on the effect of the welding environment on the dynamic recrystallization phenomenon and residual stresses during the friction stir welding process of aluminum alloy[J]. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications 235(8), 1809–1826 (2021). https://doi.org/10.1177/14644207211025113

    Article  Google Scholar 

  37. Abdollahzadeh, A., Bagheri, B., Abassi, M., et al.: Comparison of the weldability of AA6061-T6 joint under different friction stir welding conditions[J]. J. Mater. Eng. Perform. 30, 1110–1127 (2021). https://doi.org/10.1007/s11665-020-05379-4

    Article  Google Scholar 

  38. Bagheri, B., Abbasi, M., Abdolahzadeh, A., et al.: Numerical analysis of cooling and joining speed effects on friction stir welding by smoothed particle hydrodynamics (SPH)[J]. Arch. Appl. Mech. 90, 2275–2296 (2020). https://doi.org/10.1007/s00419-020-01720-4

    Article  Google Scholar 

  39. Bagheri, B., Abbasi, M., Hamzeloo, R.: Comparison of different welding methods on mechanical properties and formability behaviors of tailor welded blanks (TWB) made from AA6061 alloys[J]. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 235(12), 2225–2237 (2021)

    Article  Google Scholar 

Download references

Acknowledgements

This research is financially supported by Guangxi Science and Technology Major Program(No. AA23073019), National Natural Science Foundation of China (No. 52265004), Open Research Fund of State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Central South University (No.Kfkt2023-06), Open Fund of State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology (No. DMETKF2021017), and Innovation Project of Guangxi Graduate Education (YCSW2024052), Open Fund of High-end basic component innovation station (No. KY01080030124001), Open Fund for Academician Mao Ming's Workstation(XS-JSFW-QNKXJ-202404-007), Technology Innovation Platform Project of China Aviation Engine Group Corporation (No.CXPT-2023-044), Entrepreneurship and Innovation Talent Program of Taizhou City, Jiangsu Province.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study conception and design. M.S. is responsible for research, resource acquisition, project design, and review and editing of the manuscript. Z.Y.C. is responsible for writing the manuscript and methodology. L.Y.H. and L.W.B. are responsible for program implementation and data visualization for the research. Z.Y.S. is responsible for data analysis. Z.J.L. is responsible for exposing to the paper provides an investigation. Z.W. is responsible for supervision and guidance.

Corresponding author

Correspondence to Shuai Mo.

Ethics declarations

Conflicts of interest

Shuai Mo and Yanchen Zhang contributed equally to this manuscript, and Shuai Mo and Yanchen Zhang are co-first authors of the article. We declare that we have no conflicts with other people or organizations that can inappropriately influence our work.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mo, S., Zhang, Y., Liu, Y. et al. Nonlinear vibration and super-harmonic resonance analysis of aluminum alloy friction stir welding. Nonlinear Dyn (2024). https://doi.org/10.1007/s11071-024-09636-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11071-024-09636-2

Keywords

Navigation