Chatter prediction for uncertain parameters

doi:10.1007/s40436-018-0230-0

Advances in Manufacturing ›› 2018, Vol. 6 ›› Issue (3): 319-333.doi: 10.1007/s40436-018-0230-0

Chatter prediction for uncertain parameters

Michael Löser¹, Andreas Otto², Steffen Ihlenfeldt¹, Günter Radons²

1 Institute of Machine Tools and Control Engineering, TU Dresden, 01069 Dresden, Germany;
2 Institute of Physics, Chemnitz University of Technology, 09107 Chemnitz, Germany

收稿日期:2017-10-31 修回日期:2018-07-06 出版日期:2018-09-25 发布日期:2018-09-18
通讯作者: Michael Löser,michael.loeser@tu-dresden.de E-mail:michael.loeser@tu-dresden.de
基金资助:
Michael Löser would like to thank the German Research Foundation (DFG) for their financial support of the presented research project (Grant No. GR 1458/53-1). Andreas Otto acknowledges financial support from the German Research Foundation (DFG) (Grant No. 321138034).

Chatter prediction for uncertain parameters

Michael Löser¹, Andreas Otto², Steffen Ihlenfeldt¹, Günter Radons²

1 Institute of Machine Tools and Control Engineering, TU Dresden, 01069 Dresden, Germany;
2 Institute of Physics, Chemnitz University of Technology, 09107 Chemnitz, Germany

Received:2017-10-31 Revised:2018-07-06 Online:2018-09-25 Published:2018-09-18
Contact: Michael Löser,michael.loeser@tu-dresden.de E-mail:michael.loeser@tu-dresden.de
Supported by:
Michael Löser would like to thank the German Research Foundation (DFG) for their financial support of the presented research project (Grant No. GR 1458/53-1). Andreas Otto acknowledges financial support from the German Research Foundation (DFG) (Grant No. 321138034).

摘要/Abstract

摘要： The occurrence of chatter in milling processes was investigated in this study. The prediction of the stability lobes of metal cutting processes requires a model of the cutting force and a model of the dynamic machine tool behavior. Parameter uncertainties in the models may lead to significant differences between the predicted and measured stability behavior. One approach towards robust stability consists of running a large number of simulations with a random sample of uncertain parameters and determining the confidence levels for the chatter vibrations, which is a time-consuming task. In this paper, an efficient implementation of the multi frequency solution and the construction of an approximate solution is presented. The approximate solution requires the explicit calculation of the multi frequency solution only at a few parameter points, and the approximation error can be kept small. This study found that the calculation of the robust stability lobe diagram, which is based on the approximate solution, is significantly more efficient than an explicit calculation at all random parameter points. The numerically determined robust stability diagrams were in good agreement with the experimentally determined stability lobes.

The full text can be downloaded at https://link.springer.com/content/pdf/10.1007%2Fs40436-018-0230-0.pdf

关键词: Milling, Chatter, Uncertainties, Vibration, Stability

Abstract: The occurrence of chatter in milling processes was investigated in this study. The prediction of the stability lobes of metal cutting processes requires a model of the cutting force and a model of the dynamic machine tool behavior. Parameter uncertainties in the models may lead to significant differences between the predicted and measured stability behavior. One approach towards robust stability consists of running a large number of simulations with a random sample of uncertain parameters and determining the confidence levels for the chatter vibrations, which is a time-consuming task. In this paper, an efficient implementation of the multi frequency solution and the construction of an approximate solution is presented. The approximate solution requires the explicit calculation of the multi frequency solution only at a few parameter points, and the approximation error can be kept small. This study found that the calculation of the robust stability lobe diagram, which is based on the approximate solution, is significantly more efficient than an explicit calculation at all random parameter points. The numerically determined robust stability diagrams were in good agreement with the experimentally determined stability lobes.

The full text can be downloaded at https://link.springer.com/content/pdf/10.1007%2Fs40436-018-0230-0.pdf

Key words: Milling, Chatter, Uncertainties, Vibration, Stability

Michael Löser, Andreas Otto, Steffen Ihlenfeldt, Günter Radons. Chatter prediction for uncertain parameters[J]. Advances in Manufacturing, 2018, 6(3): 319-333.

参考文献

1. Quintana G, Ciurana J (2011) Chatter in machining processes:a review. Int J Mach Tools Manuf 51:363-376
2. Altintas Y, Weck M (2004) Chatter stability of metal cutting and grinding. CIRP Ann 53(2):619-642
3. Kong F, Yu J, Zhou X (1999) Analysis of fuzzy dynamic characteristics of machine cutting process:fuzzy stability analysis in regenerative-type-chatter. Int J Mach Tools Manuf 39:1299-1309
4. Kong F, Yu J (2007) Study of fuzzy stochastic limited cutting width on chatter. Int J Adv Manuf Technol 33(7):677-683
5. Sims N, Manson G, Mann B (2010) Fuzzy stability analysis of regenerative chatter in milling. J Sound Vib 329:1025-1041
6. Hamann D, Walz NP, Fischer A et al (2018) Fuzzy arithmetical stability analysis of uncertain machining systems. Mech Syst Signal Proc 98:534-547
7. Park SS, Qin YM (2007) Robust regenerative chatter stability in machine tools. Int J Adv Manuf Technol 33:389-402
8. Totis G (2009) RCPM-a new method for robust chatter prediction in milling. Int J Mach Tools Manuf 49:273-284
9. Hajdu D, Insperger T, Stepan G (2017) Robust stability analysis of machining operations. Int J Adv Manuf Technol 88:45-54
10. Insperger T, Lehotzky D, Stepan G (2015) Regenerative delay, parametric forcing and machine tool chatter:a review. IFACPapersOnLine 48(12):322-327
11. Lehotzky D, Insperger T, Khasawneh F et al (2017) Spectral element method for stability analysis of milling processes with discontinuous time-periodicity. Int J Adv Manuf Technol 89:2503-2514
12. Butcher EA, Bobrenkov OA, Bueler E et al (2009) Analysis of milling stability by the Chebychev collocation method:algorithm and optimal stable immersion levels. J Comput Nonlinear Dyn 4:031003
13. Budak E, Altintas Y (1998) Analytical prediction of chatter stability in milling-part I:general formulation. J Dyn Syst Meas Contr 120(1):22-30
14. Altintas Y, Stepan G, Merdol D et al (2008) Chatter stability of milling in frequency and discrete time domain. CIRP J Manuf Sci Technol 1:35-44
15. Merdol S, Altintas Y (2004) Multi frequency solution of chatter stability for low immersion milling. J Manuf Sci Eng 126:459-466
16. Löser M, Großmann K (2016) Influence of parameter uncertainties on the computation of stability lobe diagrams. Procedia CIRP 46:460-463
17. Otto A, Rauh S, Kolouch M et al (2014) Extension of Tlusty's law for the identification of chatter stability lobes in multi-dimensional cutting processes. Int J Mach Tools Manuf 82:50-58
18. Otto A, Radons G (2015) Stability analysis of machine-tool vibrations in the frequency domain. IFAC-PapersOnLine 48(12):328-333
19. Otto A, Rauh S, Ihlenfeldt S et al (2017) Stability of milling with non-uniform pitch and variable helix tools. Int J Adv Manuf Technol 89:2613-2625
20. Großmann K, Löser M, Peukert C (2012) Frequenzgangermittlung an einer rotierenden spindel. ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb 107(4):240-243
21. Cao Y, Altintas Y (2007) Modeling of spindle-bearing and machine tool systems for virtual simulation of milling operations. Int J Mach Tools Manuf 47:1342-1350
22. Rantatalo M, Aidanpää JO, Göransson B et al (2007) Milling machine spindle analysis using FEM and non-contact spindle excitation and response measurement. Int J Mach Tools Manuf 47:1034-1045
23. Biermann D, Surmann T, Kehl G (2008) Oszillatormodell für Werkzeugmaschinen zur Simulation von Zerspanprozessen. wtonline 98(3):185-190
24. Insperger T, Stepan G, Bayly PV et al (2003) Multiple chatter frequencies in milling processes. J Sound Vib 262:333-345

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Chatter prediction for uncertain parameters

Chatter prediction for uncertain parameters

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