Abstract
Chatter vibration has been a critical phenomenon in milling, and results in poor surface finishes, severe tool wear and shrill noise, which are usually overcome with quite conservative cutting parameters and hence the machining efficiency is significantly affected. In order to suppress the chatter vibration and improve the machining efficiency of milling process, a milling chatter mitigation method is presented with projection-based robust adaptive controller and an active magnetic bearing (AMB) installed in the milling spindle. The AMB is utilized to apply the active force to stabilize the milling process when the originally selected cutting conditions are unstable, with which the chatter-free boundary can be enlarged. Considering the possible parameters’ uncertainties of milling system which result from the nonlinear dynamic behaviors of the spindle system and the possible saturation of actuator caused by the noise, a projection-based robust adaptive controller is designed. Simulations of active chatter mitigation with different degrees of milling system’s uncertainties are performed, and the results show that the boundary of stability lobes diagram (SLD) of milling chatter is significantly enlarged. In addition, the milling experiments are also performed with the AMB installed in a milling spindle, and the results show that the chatter vibration is exactly mitigated with the presented method in this paper.
Similar content being viewed by others
References
Altintas, Y., & Weck, M. (2004). Chatter stability of metal cutting and grinding. CIRP Annals - Manufacturing Technology, 53, 619–642. https://doi.org/10.1016/S0007-8506(07)60032-8
Quintana, G., & Ciurana, J. (2011). Chatter in machining processes: A review. International Journal of Machine Tools and Manufacture, 51, 363–376. https://doi.org/10.1016/j.ijmachtools.2011.01.001
Munoa, J., Beudaert, X., Dombovari, Z., et al. (2016). Manufacturing Technology Chatter suppression techniques in metal cutting. CIRP Annals - Manufacturing Technology, 65, 785–808. https://doi.org/10.1016/j.cirp.2016.06.004
Devor, E. (2002). Floquet theory based approach for stability analysis of the uariable speed process. Journal of manufacturing science and engineering, 124, 10–17.
Yamato, S., Ito, T., Matsuzaki, H., & Kakinuma, Y. (2018). Programmable optimal design of sinusoidal spindle speed variation for regenerative chatter suppression. Procedia Manufacturing, 18, 152–160. https://doi.org/10.1016/j.promfg.2018.11.020
Hahn, R. (1953). Metal-cutting chatter and its elimination. Transactions of ASME, 75, 1073.
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. Precision Engineering, 47, 459–468. https://doi.org/10.1016/j.precisioneng.2016.09.021
Zeng, S., Wan, X., Li, W., et al. (2012). A novel approach to fixture design on suppressing machining vibration of flexible workpiece. International Journal of Machine Tools and Manufacture, 58, 29–43. https://doi.org/10.1016/j.ijmachtools.2012.02.008
Ziegert, J. C., Stanislaus, C., Schmitz, T. L., & Sterling, R. (2006). Enhanced damping in long slender end mills. Journal of Manufacturing Processes, 8, 39–46. https://doi.org/10.1016/S1526-6125(06)70100-1
Yang, Y., Muñoa, J., & Altintas, Y. (2010). Optimization of multiple tuned mass dampers to suppress machine tool chatter. International Journal of Machine Tools and Manufacture, 50, 834–842. https://doi.org/10.1016/j.ijmachtools.2010.04.011
Zhang, Z., Li, H., Meng, G., & Ren, S. (2017). Milling chatter suppression in viscous fluid: A feasibility study. International Journal of Machine Tools and Manufacture, 120, 20–26. https://doi.org/10.1016/j.ijmachtools.2017.02.005
Chen, F., Lu, X., & Altintas, Y. (2014). A novel magnetic actuator design for active damping of machining tools. International Journal of Machine Tools and Manufacture, 85, 58–69. https://doi.org/10.1016/j.ijmachtools.2014.05.004
Mei, D., Kong, T., Shih, A. J., & Chen, Z. (2009). Magnetorheological fluid-controlled boring bar for chatter suppression. Journal of Materials Processing Technology, 209, 1861–1870. https://doi.org/10.1016/j.jmatprotec.2008.04.037
Knospe, C. R. (2004). Active magnetic bearings for machining applications. IFAC Proceedings, 37, 7–12. https://doi.org/10.1016/S1474-6670(17)31072-8
Wu, Y., Zhang, H. T., Huang, T., et al. (2016). Adaptive chatter mitigation control for machining processes with input saturations. International Journal of Robust and Nonlinear Control, 26, 3088–3100. https://doi.org/10.1002/rnc.3493
Paul, S., & Morales-Menendez, R. (2018). Active control of chatter in milling process using intelligent PD/PID control. IEEE Access, 6, 72698–72713. https://doi.org/10.1109/ACCESS.2018.2882491
Zhang, H., Chen, Z., & Ding, H. (2013). Adaptive LQR control to attenuate chatters. In International conference on intelligent robotics and applications (pp 525–534). Springer.
Zhang, H. T., Wu, Y., He, D., & Zhao, H. (2015). Model predictive control to mitigate chatters in milling processes with input constraints. International Journal of Machine Tools and Manufacture, 91, 54–61. https://doi.org/10.1016/j.ijmachtools.2015.01.002
Li, D., Cao, H., Zhang, X., et al. (2019). Model predictive control based active chatter control in milling process. Mechanical Systems and Signal Processing, 128, 266–281. https://doi.org/10.1016/j.ymssp.2019.03.047
Monnin, J., Kuster, F., & Wegener, K. (2014). Optimal control for chatter mitigation in milling-Part 1: modeling and control design. Control Engineering Practice, 24, 156–166. https://doi.org/10.1016/j.conengprac.2013.11.010
Monnin, J., Kuster, F., & Wegener, K. (2014). Optimal control for chatter mitigation in milling-Part 2: Experimental validation. Control Engineering Practice, 24, 167–175. https://doi.org/10.1016/j.conengprac.2013.11.011
Moradi, H., Vossoughi, G., Movahhedy, M. R., & Salarieh, H. (2013). Suppression of nonlinear regenerative chatter in milling process via robust optimal control. Journal of Process Control, 23, 631–648. https://doi.org/10.1016/j.jprocont.2013.02.006
Abele, E., Altintas, Y., & Brecher, C. (2010). Machine tool spindle units. CIRP Annals - Manufacturing Technology, 59, 781–802. https://doi.org/10.1016/j.cirp.2010.05.002
Munoa, J., Beudaert, X., Dombovari, Z., et al. (2016). Chatter suppression techniques in metal cutting. CIRP Annals - Manufacturing Technology, 65, 785–808. https://doi.org/10.1016/j.cirp.2016.06.004
Altintas, Y. (2012). Manufacturing automation: Metal cutting mechanics, machine tool vibrations, and CNC design. Cambridge University Press.
Altintaş, Y., & Budak, E. (1995). Analytical prediction of stability lobes in milling. CIRP Annals - Manufacturing Technology, 44, 357–362. https://doi.org/10.1016/S0007-8506(07)62342-7
Insperger, T., & Stépán, G. (2004). Updated semi-discretization method for periodic delay-differential equations with discrete delay. International Journal for Numerical Methods in Engineering, 61, 117–141. https://doi.org/10.1002/nme.1061
Schweitzer, G., & Maslen, E. H. (2009). Magnetic bearings: Theory, design, and application to rotating machinery. Springer.
Wan, S., Li, X., Su, W., et al. (2019). Active damping of milling chatter vibration via a novel spindle system with an integrated electromagnetic actuator. Precision Engineering, 57, 203–210. https://doi.org/10.1016/j.precisioneng.2019.04.007
Lavretsky, E., & Lavretsky, E. (2012). Robust and adaptive control : With aerospace applications. Springer.
Min, Y., & Liu, Y. (2007). Barbalat Lemma and its application in analysis of system stability. Journal of Shang Dong University, 37, 51–55.
Wan, S., Hong, J., & Su, W., et al. (2017). Measurement of dynamic performances of high-speed rotating spindle by non-contact electromagnetic loading device. In ASME international mechanical engineering congress and exposition, proceedings (IMECE).
Wan, S., Li, X., Su, W., & Hong, J. (2019). Investigation on adaptive filter for on-line detection and active control of chatter vibration in milling process. In Proceedings of the ASME design engineering technical conference.
Wan, S., Li, X., Chen, W., & Hong, J. (2018). Investigation on milling chatter identification at early stage with variance ratio and Hilbert-Huang transform. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-017-1410-y
Acknowledgements
This work was supported by National Natural Science Foundation of China (No. 52075428 & No. 52105273), Natural Science Basic Research Plan in Shaanxi Province of China (No. 2021JQ-038), Two-chain Fusion high-end machine tool projects of Shaanxi Province (2021LLRh-01-02), and China Postdoctoral Science Foundation (No. 2021M6925543). The authors express their gratitude for the supports. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Author information
Authors and Affiliations
Corresponding author
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 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.
About this article
Cite this article
Wan, S., Li, X., Su, W. et al. Milling Chatter Mitigation with Projection-Based Robust Adaptive Controller and Active Magnetic Bearing. Int. J. Precis. Eng. Manuf. 23, 1453–1463 (2022). https://doi.org/10.1007/s12541-022-00710-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12541-022-00710-6