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Displacement difference feedback control of chatter in milling processes

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Abstract

Chatter is an unfavorable phenomenon that commonly occurs in the machining process, which results in various problems such as poorly finished surfaces, short tool life, and low machining efficiency. Thus, based on the intelligent manufacturing paradigm, an active chatter control strategy is proposed in this work. Different from the commonly used control methods, which strive to reduce the whole vibration (i.e., stable and chatter vibrations) during the machining process, the proposed strategy focuses on suppressing the chatter component by feeding back the displacement difference of the spindle-tool system at the current time and one tooth passing period before. On the basis of the proposed chatter control concept, a piezoelectric actuator-based active chatter control intelligent spindle-tool system as well as a proportional-differential (PD) controller and a fuzzy controller are designed to perform numerical simulations and milling experiments with different cutting parameters. The results prove that the developed strategies not only successfully control chatter and increase the maximum material removal rate (MRR) but also significantly decrease the required voltage of the actuator, which is conducive to saving control energy.

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The data analyzed in this work is included in this published paper.

References

  1. Munoa J, Beudaert X, Dombovari Z, Altintas Y, Budak E, Brecher C, Stepan G (2016) Chatter suppression techniques in metal cutting. CIRP Ann-Manuf Technol 65:785–808. https://doi.org/10.1016/j.cirp.2016.06.004

    Article  Google Scholar 

  2. Abele E, Altintas Y, Brecher C (2010) Machine tool spindle units. CIRP Ann-Manuf Technol 59:781–802. https://doi.org/10.1016/j.cirp.2010.05.002

    Article  Google Scholar 

  3. Zhu L, Liu C (2020) Recent progress of chatter prediction, detection and suppression in milling. Mech Syst Signal Pr 143:106840. https://doi.org/10.1016/j.ymssp.2020.106840

    Article  Google Scholar 

  4. Tehranizadeh F, Koca R, Budak E (2019) Investigating effects of serration geometry on milling forces and chatter stability for their optimal selection. Int J Mach Tool Manuf 144:103425. https://doi.org/10.1016/j.ijmachtools.2019.103425

  5. Stepan G, Hajdu D, Iglesias A, Takacs D, Dombovari Z (2018) Ultimate capability of variable pitch milling cutters. CIRP Ann-Manuf Technol 67:373–376. https://doi.org/10.1016/j.cirp.2018.03.005

    Article  Google Scholar 

  6. Hayasaka T, Ito A, Shamoto E (2017) Generalized design method of highly-varied-helix end mills for suppression of regenerative chatter in peripheral milling. Precis Eng 48:45–59. https://doi.org/10.1016/j.precisioneng.2016.11.004

    Article  Google Scholar 

  7. Otto A, Rauh S, Ihlenfeldt S, Radons G (2017) Stability of milling with non-uniform pitch and variable helix tools. Int J Adv Manuf Technol 89:2613–2625. https://doi.org/10.1007/s00170-016-9762-2

    Article  Google Scholar 

  8. Comak A, Budak E (2017) Modeling dynamics and stability of variable pitch and helix milling tools for development of a design method to maximize chatter stability. Precis Eng 47:459–468. https://doi.org/10.1016/j.precisioneng.2016.09.021

    Article  Google Scholar 

  9. Ma W, Yang Y, Jin X (2021) Chatter suppression in micro-milling using shank-mounted two-DOF tuned mass damper. Precis Eng 72:144–157. https://doi.org/10.1016/j.precisioneng.2021.04.017

    Article  Google Scholar 

  10. Moradi H, Bakhtiari-Nejad F, Movahhedy MR, Vossoughi G (2012) Stability improvement and regenerative chatter suppression in nonlinear milling process via tunable vibration absorber. J Sound Vib 331:4668–4690. https://doi.org/10.1016/j.jsv.2012.05.032

    Article  Google Scholar 

  11. Habib G, Kerschen G, Stepan G (2017) Chatter mitigation using the nonlinear tuned vibration absorber. Int J Nonlinear Mech 91:103–112. https://doi.org/10.1016/j.ijnonlinmec.2017.02.014

    Article  Google Scholar 

  12. Yang Y, Muñoa J, Altintas Y (2010) Optimization of multiple tuned mass dampers to suppress machine tool chatter. Int J Mach Tool Manuf 50:834–842. https://doi.org/10.1016/j.ijmachtools.2010.04.011

    Article  Google Scholar 

  13. Cao H, Zhang X, Chen X (2017) The concept and progress of intelligent spindles: a review. Int J Mach Tool Manu 112:21–52. https://doi.org/10.1016/j.ijmachtools.2016.10.005

    Article  Google Scholar 

  14. Monnin J, Kuster F, Wegener K (2014) Optimal control for chatter mitigation in milling—part 2: experimental validation. Control Eng Pract 24:167–175. https://doi.org/10.1016/j.conengprac.2013.11.011

    Article  Google Scholar 

  15. Monnin J, Kuster F, Wegener K (2014) Optimal control for chatter mitigation in milling—part 1: modeling and control design. Control Eng Pract 24:156–166. https://doi.org/10.1016/j.conengprac.2013.11.010

    Article  Google Scholar 

  16. Zaeh M, Kleinwort R, Fagerer P, Altintas Y (2017) Automatic tuning of active vibration control systems using inertial actuators. CIRP Ann-Manuf Technol 66:365–368. https://doi.org/10.1016/j.cirp.2017.04.051

    Article  Google Scholar 

  17. Lu X, Chen F, Altintas Y (2014) Magnetic actuator for active damping of boring bars. CIRP Ann-Manuf Technol 63:369–372. https://doi.org/10.1016/j.cirp.2014.03.127

    Article  Google Scholar 

  18. Li D, Cao H, Zhang X, Chen X, Yan R (2019) Model predictive control based active chatter control in milling process. Mech Syst Signal Pr 128:266–281. https://doi.org/10.1016/j.ymssp.2019.03.047

    Article  Google Scholar 

  19. Li D, Cao H, Liu J, Zhang X, Chen X (2019) Milling chatter control based on asymmetric stiffness. Int J Mach Tool Manuf 147:103458. https://doi.org/10.1016/j.ijmachtools.2019.103458

  20. Ma H, Wu J, Yang L, Xiong Z (2017) Active chatter suppression with displacement-only measurement in turning process. J Sound Vib. https://doi.org/10.1016/j.jsv.2017.05.009

    Article  Google Scholar 

  21. Li X, Wan S, Yuan J, Yin Y, Hong J (2021) Active suppression of milling chatter with LMI-based robust controller and electromagnetic actuator. J Mater Process Technol. https://doi.org/10.1016/j.jmatprotec.2021.117238

    Article  Google Scholar 

  22. Wan S, Li X, Su W, Yuan J, Hong J, Jin X (2019) Active damping of milling chatter vibration via a novel spindle system with an integrated electromagnetic actuator. Precis Eng 57:203–210. https://doi.org/10.1016/j.precisioneng.2019.04.007

    Article  Google Scholar 

  23. Chen Z, Zhang H-T, Zhang X, Ding H (2014) Adaptive active chatter control in milling processes. J Dyn Syst Meas Control 136:021007. https://doi.org/10.1115/1.4025694

  24. Wu Y, Zhang H-T, Huang T, Ren G, Ding H (2018) Robust chatter mitigation control for low radial immersion machining processes. IEEE Trans Autom Sci Eng 15:1972–1979. https://doi.org/10.1109/TASE.2018.2838152

    Article  Google Scholar 

  25. Chen F, Lu X, Altintas Y (2014) A novel magnetic actuator design for active damping of machining tools. Int J Mach Tool Manuf 85:58–69. https://doi.org/10.1016/j.ijmachtools.2014.05.004

    Article  Google Scholar 

  26. Mancisidor I, Pena-Sevillano A, Dombovari Z, Barcena R, Munoa J (2019) Delayed feedback control for chatter suppression in turning machines. Mechatronics 63:102276. https://doi.org/10.1016/j.mechatronics.2019.102276

    Article  Google Scholar 

  27. Dijk NJMV, Wouw NVD, Doppenberg EJJ, Han AJO, Nijmeijer H (2012) Robust active chatter control in the high-speed milling process. IEEE T Contr Syst T 20:901–917. https://doi.org/10.1109/TCST.2011.2157160

    Article  Google Scholar 

  28. Wouw NVD, Dijk NJMV, Schiffler A, Nijmeijer H, Abele E (2017). Experimental validation of robust chatter control for high-speed milling processes: Springer International Publishing. https://doi.org/10.1007/978-3-319-53426-8_21

    Article  Google Scholar 

  29. Li D, Cao H, Chen X (2021) Fuzzy control of milling chatter with piezoelectric actuators embedded to the tool holder. Mech Syst Signal Pr 148:107190. https://doi.org/10.1016/j.ymssp.2020.107190

    Article  Google Scholar 

  30. van de Wouw N, van Dijk N, Nijmeijer H (2015) Pyragas-type feedback control for chatter mitigation in high-speed milling. IFAC-PapersOnLine 48:334–339. https://doi.org/10.1016/j.ifacol.2015.09.400

    Article  Google Scholar 

  31. Zhang H, Liu D (2006) Fuzzy modeling and fuzzy control: Springer Science & Business Media

  32. Driankov D, Hellendoorn H, Reinfrank M (2013) An introduction to fuzzy control: Springer Science & Business Media

  33. Altintas Y (2012) Manufacturing automation: metal cutting mechanics, machine tool vibrations, and CNC design: Cambridge university press. https://doi.org/10.1115/1.1399383

  34. Castillo O, Cervantes L, Soria J, Sanchez MA, Castro JR (2016) A generalized type-2 fuzzy granular approach with applications to aerospace. Inf Sci 354:165–177. https://doi.org/10.1016/j.ins.2016.03.001

    Article  Google Scholar 

  35. Pour DS, Behbahani S (2016) Semi-active fuzzy control of machine tool chatter vibration using smart MR dampers. Int J Adv Manuf Technol 83:421–428. https://doi.org/10.1007/s00170-015-7503-6

    Article  Google Scholar 

  36. Özşahin O, Özgüven HN, Budak E (2010) Analysis and compensation of mass loading effect of accelerometers on tool point FRF measurements for chatter stability predictions. Int J Mach Tool Manuf 50:585–589. https://doi.org/10.1016/j.ijmachtools.2010.02.002

    Article  Google Scholar 

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Funding

This work is supported by the National Natural Science Foundation of China (No. 51922084).

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Authors and Affiliations

  1. State Key Laboratory in Ultra-Precision Machining Technology, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, People’s Republic of China

    Denghui Li

  2. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, People’s Republic of China

    Hongrui Cao & Xuefeng Chen

Authors
  1. Denghui Li
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  2. Hongrui Cao
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  3. Xuefeng Chen
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Contributions

Denghui Li: conceptualization, methodology, software, validation, and writing–original draft. Hongrui Cao: conceptualization, writing–review and editing, supervision, project administration, and funding acquisition. (3) Xuefeng Chen: investigation, resources, and writing–review and editing.

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Correspondence to Hongrui Cao.

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Li, D., Cao, H. & Chen, X. Displacement difference feedback control of chatter in milling processes. Int J Adv Manuf Technol 120, 6053–6066 (2022). https://doi.org/10.1007/s00170-022-09128-w

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