Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-21T16:06:11.390Z Has data issue: false hasContentIssue false
  • English
  • Français

Smooth toolpath interpolation for a 5-axis hybrid machine tool

Published online by Cambridge University Press:  27 July 2022

Zhen He Open the ORCID record for Zhen He [Opens in a new window] ,
Hanliang Fang Open the ORCID record for Hanliang Fang [Opens in a new window] ,
Yufei Bao Open the ORCID record for Yufei Bao [Opens in a new window] ,
Fufu Yang Open the ORCID record for Fufu Yang [Opens in a new window]  and
Jun Zhang Open the ORCID record for Jun Zhang [Opens in a new window]
Zhen He
Affiliation:
School of Mechanical Engineering and Automation, Fuzhou University, Fujian 350116, China
Hanliang Fang
Affiliation:
School of Mechanical Engineering and Automation, Fuzhou University, Fujian 350116, China
Yufei Bao
Affiliation:
School of Mechanical Engineering and Automation, Fuzhou University, Fujian 350116, China
Fufu Yang
Affiliation:
School of Mechanical Engineering and Automation, Fuzhou University, Fujian 350116, China
Jun Zhang*
Affiliation:
School of Mechanical Engineering and Automation, Fuzhou University, Fujian 350116, China The State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China
*
*Corresponding author. E-mail: zhang_jun@fzu.edu.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

Due to the merits of high rigidity and good dynamics, hybrid machine tools have been gradually applied to efficient machining of thin-walled workpiece with complex geometries. However, the discontinuity of tangential component of toolpath in hybrid machine tools may cause velocity fluctuations, leading to poor surface quality of workpiece. In this paper, a novel 5-axis hybrid machine tool is taken as an example to demonstrate a smooth toolpath interpolation method. First, an adaptive acceleration and deceleration control algorithm is presented to realize the smooth transition between two constrained velocity points. Second, a spline curve-based interpolation algorithm is proposed to realize the smoothness of the trajectory. Meanwhile, a parameter synchronization method is proposed to ensure the synchronization of the interpolated tool-axis vector and the interpolated tool tip. Thirdly, an inverse kinematic analysis is conducted based on an inverse position solution model and a velocity mapping model. Finally, a set of machining tests on S-shape workpiece in line with the ISO standard is carried out to verify the effectiveness of the proposed smooth toolpath interpolation method.

Keywords

hybrid machine toolinverse kinematicstrajectory controlvelocity controlsmooth toolpath
Type
Research Article
Information
Robotica , Volume 40 , Issue 12 , December 2022 , pp. 4431 - 4454
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amanullah, A., Murshiduzzaman, T. S. and Khan, R., “Design and development of a hybrid machine combining rapid prototyping and CNC milling operation,” Proc. Eng. 184(4), 163–170 (2017).10.1016/j.proeng.2017.04.081CrossRefGoogle Scholar
Song, Y., Wu, J., Yu, G. and Huang, T., “Dynamic characteristic prediction of a 5-DOF hybrid machine tool by using scale model considering the geometric distortion of bearings,” Mech. Mach. Theory 145(4), 103679 (2020).10.1016/j.mechmachtheory.2019.103679CrossRefGoogle Scholar
Liu, Q. and Huang, T., “Inverse kinematics of a 5-axis hybrid robot with non-singular toolpath generation,” Robot Comput.-Integr. Manuf. 56(2), 140–148 (2019).10.1016/j.rcim.2018.06.003CrossRefGoogle Scholar
Hennes, N. and Staimer, D., “Application of PKM in Aerospace Manufacturing-High Performance Machining Centers ECOSPEED, ECOSPEED-F and ECOLINER,” In: Proc. 4th Chemnitz Parallel Kinematics Semin , Chemnitz, Germany (2004) pp. 557–577.Google Scholar
Hao, C., Rakha, H. A., Loulizi, A., El-Shawarby, I. and Almannaa, M. H., “Development and preliminary field testing of an In-Vehicle Eco-Speed control system in the vicinity of signalized intersections,” IFAC-PapersOnLine 49(3), 249–254 (2016).Google Scholar
Ruiz, A., Campa, F. J., Roldán-Paraponiaris, C., Altuzarra, O. and Pinto, C., “Experimental validation of the kinematic design of 3-PRS compliant parallel mechanisms,” Mechatronics 39, 77–88 (2016).10.1016/j.mechatronics.2016.08.006CrossRefGoogle Scholar
Jose, L. O. and Scott, W., New PKM Tricept T9000 and Its Application to Flexible Manufacturing at Aerospace Industry, SAE International, Los Angeles, USA, 2007 Paper No. 07ATC–94.Google Scholar
Neumann, K., The key to aerospace automation. aerospace manufacturing and automated fastening conference and exhibition, Detroit, USA, Paper No. 2006-01-3144 (2006).10.4271/2006-01-3144Google Scholar
Wang, D., Wu, J., Wang, L., Liu, Y. and Yu, G., “A method for designing control parameters of a 3-DOF parallel tool head,” Mechatronics 41(2), 102–113 (2017).10.1016/j.mechatronics.2016.12.003CrossRefGoogle Scholar
Fang, H., Tang, T. and Zhang, J., “Kinematic analysis and comparison of a 2R1T redundantly actuated parallel manipulator and its non-redundantly actuated forms,” Mech. Mach. Theory 142(2), 103587 (2019).10.1016/j.mechmachtheory.2019.103587CrossRefGoogle Scholar
Jiang, S. J., Chi, C. C., Fang, H. L., Tang, T. F. and Zhang, J., “A minimal-error-model based two-step kinematic calibration methodology for redundantly actuated parallel manipulators: an application to a 3-DoF spindle head,” Mech. Mach. Theory 167(14), 104532 (2022).10.1016/j.mechmachtheory.2021.104532CrossRefGoogle Scholar
Wang, D., Wu, J., Wang, L. and Liu, Y., “A Post-Processing strategy of a 3-DOF parallel tool head based on velocity control and coarse interpolation,” IEEE Trans. Ind. Electron. 139, 1–1 (2017).Google Scholar
Shi, J., Qingzhen, B. I. and Wang, Y., “Five-Axis interpolation of continuous short linear trajectories for 3[PP]S-XY hybrid mechanism by dual bezier blending,” J. Shanghai Jiaotong Univ. Chin. (Sci.) 21(1), 90–102 (2016).10.1007/s12204-015-1688-6CrossRefGoogle Scholar
Xie, Z., Xie, F., Liu, X. J. and wang, J., “Global G3 continuity toolpath smoothing for a 5-DoF machining robot with parallel kinematics,” Robot Comput.-Integr. Manuf. 67, 102018 (2021).10.1016/j.rcim.2020.102018CrossRefGoogle Scholar
Wu, J., Zhou, H., Tang, X. and Chen, J., “Implementation of CL points preprocessing methodology with NURBS curve fitting technique for high-speed machining,” Comput. Ind. Eng. 81(3), 58–64 (2015).10.1016/j.cie.2014.12.018CrossRefGoogle Scholar
Sencer, B., Kakinuma, Y. and Yamada, Y., “Linear interpolation of machining tool-paths with robust vibration avoidance and contouring error control,” Precis. Eng. 66(3), 269–281 (2020). doi: 10.1016/j.precisioneng.2020.04.007.CrossRefGoogle Scholar
Tajima, S. and Sencer, B., “Accurate real-time interpolation of 5-axis tool-paths with local corner smoothing,” Int. J. Mach. Tools Manuf. 142(2), 1–15 (2019). doi: 10.1016/j.ijmachtools.2019.04.005.CrossRefGoogle Scholar
Wang, L. P. W., Li, W. T., Si, H., Yuan, X. and Liu, Y. Z., “Geometric deviation reduction method for interpolated toolpath in five-axis flank milling of the S-shaped test piece,” Proc. Inst. Mech. Eng. B J. Eng. Manuf. 234(5), 910–919 (2019).10.1177/0954405419889235CrossRefGoogle Scholar
Wang, D., Wu, J. and Wang, L. P., “A post-processing strategy of a 3-DOF parallel tool head based on velocity control and coarse interpolation,” IEEE Trans. Ind. Electron. 65(8), 6333–6342 (2017).Google Scholar
Ni, Y. B., Zhang, Y., Sun, K., Wang, H. and Sun, Y. P., “Interpolation control algorithm for a three-RPS parallel spindle head,” Proc. Inst. Mech. Eng. 230(7), 661–671 (2016).10.1177/0959651816645687Google Scholar
Shpitalni, M., Koren, Y. and Lo, C. C., “Realtime curve interpolators,” Comput. Aided Design 26(11), 832–838 (1994).Google Scholar
Zhang, J., Zhang, L., Zhang, K. and Mao, J., “Double NURBS trajectory generation and synchronous interpolation for five-axis machining based on dual quaternion algorithm,” Int. J. Adv. Manuf. Technol. 83(9-12), 2015–2025 (2016).10.1007/s00170-015-7723-9CrossRefGoogle Scholar
Li, D., Zhang, W., Zhou, W., Shang, T. and Fleischer, J., “Dual NURBS path smoothing for 5-axis linear path of flank milling,” Int. J. Precis. Eng. Manufact. 19(12), 1811–1820 (2018).10.1007/s12541-018-0209-6CrossRefGoogle Scholar
Jahanpour, J., Motallebi, M. and Porghoveh, M., “A novel trajectory planning scheme for parallel machining robots enhanced with NURBS curves,” J. Intell. Robot. Syst. 82(2), 257–275 (2016).10.1007/s10846-015-0239-6CrossRefGoogle Scholar
Shen, X., Xie, F., Liu, X. J. and Xie, Z., “A smooth and undistorted toolpath interpolation method for 5-DoF parallel kinematic machines,” Robot Comput.-Integr. Manuf. 57, 347–356 (2019).10.1016/j.rcim.2018.12.013CrossRefGoogle Scholar
Yang, J. X., Deniz, A. and Yusuf, A., “A feedrate scheduling algorithm to constrain tool tip position and tool orientation errors of five-axis CNC machining under cutting load disturbances,” CIRP J. Manuf. Sci. Technol. 23(2), 78–90 (2018).10.1016/j.cirpj.2018.08.005Google Scholar
Shingo, T. and Burak, S., “Global tool-path smoothing for CNC machine tools with uninterrupted acceleration,” Int. J. Mach. Tool Manuf. 121(1), 81–95 (2017).Google Scholar
Liu, X., Li, Y. G. and Li, Q., “A region-based 3+2-axis machining toolpath generation method for freeform surface,” Int. J. Adv. Manuf. Technol. 97(1-4), 1149–1163 (2018).10.1007/s00170-018-1982-1CrossRefGoogle Scholar
Chu, C. H., Chen, H. Y. and Chang, C. H., “Continuity-preserving toolpath generation for minimizing machining errors in five-axis CNC flank milling of ruled surfaces,” J. Manuf. Syst. 55(5-8), 171–178 (2020).10.1016/j.jmsy.2020.03.004CrossRefGoogle Scholar
Zhao, K., Li, S. and Kang, Z., “Smooth minimum time trajectory planning with minimal feed fluctuation,” Int. J. Adv. Manuf. Tech. 9-12(1-4), 1–13 (2019).10.1007/s00170-018-3182-4CrossRefGoogle Scholar
Lee, A. C., Lin, M. T., Pan, Y. R. and Liu, W. Y., “The feedrate scheduling of NURBS interpolator for CNC machine tools,” Comput. Aided Design 43(6), 612–628 (2011).10.1016/j.cad.2011.02.014CrossRefGoogle Scholar
Liu, M., Huang, Y., Yin, L., Guo, J. W., Shao, X. Y. and Zhang, G. J., “Development and implementation of a NURBS interpolator with smooth feedrate scheduling for CNC machine tools,” Int. J. Mach. Tools Manuf. 87(1–2), 1–15 (2014).10.1016/j.ijmachtools.2014.07.002CrossRefGoogle Scholar
Javad, J., Mehdi, M. and Mojtaba, P., “A novel trajectory planning scheme for parallel machining robots enhanced with NURBS curves,” J. Intell. Robot. Syst. 82(2), 257–275 (2016).Google Scholar
Yeh, S. S. and Hsu, P. L., “Adaptive-feedrate interpolation for parametric curves with a confined chord error,” Comput. Aided Design 34(3), 229–237 (2002).10.1016/S0010-4485(01)00082-3CrossRefGoogle Scholar
Feng, J., Li, Y., Wang, Y. and Chen, M., “Design of a real-time adaptive NURBS interpolator with axis acceleration limit,” Int. J. Adv. Manuf. Tech. 48(1-4), 227–241 (2010).10.1007/s00170-009-2261-yCrossRefGoogle Scholar
Du, X., Jie, H. and Zhu, L. M., “A complete S-shape feed rate scheduling approach for NURBS interpolator,” J. Comput. Des. Eng. 2(4), 206–217 (2015).Google Scholar
Yuxiang, X. U., Xiaoguang, X. U. and Zhu, X., “Manipulator speed planning strategy based on the Five-segment S-curve,” J. Sichuan Univ. Sci. Eng. 30(2), 37–41 (2017).Google Scholar
Geng, C., Yu, D., Zheng, L., Zhang, H. and Wang, F., “A tool path correction and compression algorithm for five-axis CNC machining,” J. Syst. Sci. Comp. 26(5), 799–816 (2013).10.1007/s11424-013-3101-6CrossRefGoogle Scholar