A new method using double distributed joint interface model for three-dimensional dynamics prediction of spindle-holder-tool system

The cutting process stability strongly depends on dynamics of the spindle-holder-tool system, which often changes and is determined by impact hammer testing in general. In order to avoid repeated and time-consuming impact hammer testing on different spindle-holder-tool combinations, this paper proposes a new method for three-dimensional dynamics prediction of spindle-holder-tool system. The system is modeled using Timoshenko’s beam theory and substructure synthesis method. The tool-holder connection is regarded as a double distributed joint interface model including a collet, a holder-collet joint interface and a tool-collet joint interface. The two joint interfaces are further modeled as two sets of independent spring-damper elements, while the collet and tool are modeled as Timoshenko beams with varying cross-sections. The substructure synthesis method is adopted to obtain the equation of motion of the spindle-holder-tool system. Finally, experiments of bending, torsional, and axial FRFs are carried out to verify the proposed method. Good agreements show that the new method is capable of predicting tool point FRFs more accurately compared with the existing methods.

[1]  Takashi Yokoyama,et al.  Vibrations of a hanging Timoshenko beam under gravity , 1990 .

[2]  Yusuf Altintas,et al.  Prediction of frequency response function (FRF) of asymmetric tools from the analytical coupling of spindle and beam models of holder and tool , 2015 .

[3]  Zhijun Wu,et al.  An efficient experimental approach to identify tool point FRF by improved receptance coupling technique , 2018 .

[4]  Hamid Ahmadian,et al.  Tool point dynamics prediction by a three-component model utilizing distributed joint interfaces , 2010 .

[5]  Tony L. Schmitz,et al.  Shrink fit tool holder connection stiffness/damping modeling for frequency response prediction in milling , 2007 .

[6]  Min Wan,et al.  An improved method for tool point dynamics analysis using a bi-distributed joint interface model , 2016 .

[7]  Min Wan,et al.  Study on the construction mechanism of stability lobes in milling process with multiple modes , 2015 .

[8]  Hamid Ahmadian,et al.  Modelling machine tool dynamics using a distributed parameter tool–holder joint interface , 2007 .

[9]  Zhengjia He,et al.  Chatter stability of milling with speed-varying dynamics of spindles , 2012 .

[10]  Berend Denkena,et al.  Receptance coupling based algorithm for the identification of contact parameters at holder–tool interface , 2016 .

[11]  Yusuf Altintas,et al.  Modeling and identification of tool holder–spindle interface dynamics , 2007 .

[12]  T. Aida,et al.  Dynamic behavior of railway bridges under unsprung masses of a multi-vehicle train , 1990 .

[13]  Xuefeng Chen,et al.  The concept and progress of intelligent spindles: A review , 2017 .

[14]  Bin Qi,et al.  Tool point frequency response function prediction using RCSA based on Timoshenko beam model , 2017 .

[15]  Uttara Kumar,et al.  Modeling and experimentation for three-dimensional dynamics of endmills , 2012 .

[16]  Bing Li,et al.  Finite Element Model Updating of Machine-Tool Spindle Systems , 2013 .

[17]  Mohammad R. Movahhedy,et al.  Prediction of spindle dynamics in milling by sub-structure coupling , 2006 .

[18]  Gianni Campatelli,et al.  Improved RCSA technique for efficient tool-tip dynamics prediction , 2016 .

[19]  H. Nevzat Özgüven,et al.  Structural modifications using frequency response functions , 1990 .

[20]  Tony L. Schmitz,et al.  Three-Component Receptance Coupling Substructure Analysis for Tool Point Dynamics Prediction , 2005 .

[21]  Zhijun Wu,et al.  Milling stability prediction for flexible workpiece using dynamics of coupled machining system , 2017 .

[22]  Ma Yingchao,et al.  Generalized method for the analysis of bending, torsional and axial receptances of tool–holder–spindle assembly , 2015 .

[23]  Erhan Budak,et al.  Effect analysis of bearing and interface dynamics on tool point FRF for chatter stability in machine tools by using a new analytical model for spindle–tool assemblies , 2007 .

[24]  Weihong Zhang,et al.  Chatter prediction for the peripheral milling of thin-walled workpieces with curved surfaces , 2016 .

[25]  Chao Xu,et al.  Dynamic modeling and parameters identification of a spindle–holder taper joint , 2013 .

[26]  Wei Cheng,et al.  Model Updating of Spindle Systems Based on the Identification of Joint Dynamics , 2015 .

[27]  Tony L. Schmitz,et al.  Torsional and axial frequency response prediction by RCSA , 2010 .

[28]  Simon S. Park,et al.  Joint identification of modular tools using a novel receptance coupling method , 2008 .

[29]  Min Wan,et al.  Prediction of chatter stability for multiple-delay milling system under different cutting force models , 2011 .

[30]  Yusuf Altintas,et al.  Receptance coupling for end mills , 2003 .

[31]  Erhan Budak,et al.  Analytical modeling of spindle-tool dynamics on machine tools using Timoshenko beam model and receptance coupling for the prediction of tool point FRF , 2006 .

[32]  Michele Monno,et al.  A new receptance coupling substructure analysis methodology to improve chatter free cutting conditions prediction , 2013 .

[33]  Tony L. Schmitz,et al.  Predicting High-Speed Machining Dynamics by Substructure Analysis , 2000 .

[34]  Evren Burcu Kivanc,et al.  Structural modeling of end mills for form error and stability analysis , 2004 .

[35]  Yusuf Altintas,et al.  Analytical Prediction of Stability Lobes in Milling , 1995 .

[36]  Gábor Stépán,et al.  Updated semi‐discretization method for periodic delay‐differential equations with discrete delay , 2004 .

[37]  Tony L. Schmitz,et al.  Receptance coupling for dynamics prediction of assemblies with coincident neutral axes , 2006 .

[38]  Jokin Munoa,et al.  Receptance coupling for tool point dynamic prediction by fixed boundaries approach , 2014 .

[39]  B. Mann,et al.  Stability of Interrupted Cutting by Temporal Finite Element Analysis , 2003 .