Improved time-optimal B-spline feedrate scheduling for NURBS tool paths in CNC machining

Yang Li , Fu-Sheng Liang , Lei Lu , Cheng Fan

Advances in Manufacturing ›› 2023, Vol. 11 ›› Issue (1) : 111 -129.

PDF
Advances in Manufacturing ›› 2023, Vol. 11 ›› Issue (1) : 111 -129. DOI: 10.1007/s40436-022-00413-1
Article

Improved time-optimal B-spline feedrate scheduling for NURBS tool paths in CNC machining

Author information +
History +
PDF

Abstract

Feedrate scheduling in computer numerical control (CNC) machining is of great importance to fully develop the capabilities of machine tools while maintaining the motion stability of each actuator. Smooth and time-optimal feedrate scheduling plays a critical role in improving the machining efficiency and precision of complex surfaces considering the irregular curvature characteristics of tool paths and the limited drive capacities of machine tools. This study develops a general feedrate scheduling method for non-uniform rational B-splines (NURBS) tool paths in CNC machining aiming at minimizing the total machining time without sacrificing the smoothness of feed motion. The feedrate profile is represented by a B-spline curve to flexibly adapt to the frequent acceleration and deceleration requirements of machining along complex tool paths. The time-optimal B-spline feedrate is produced by continuously increasing the control points sequentially from zero positions in the bidirectional scanning and sampling processes. The required number of knots for the time-optimal B-spline feedrate can be determined using a progressive knot insertion method. To improve the computational efficiency, the B-spline feedrate profile is divided into a series of independent segments and the computation in each segment can be performed concurrently. The proposed feedrate scheduling method is capable of dealing with not only the geometry constraints but also high-order drive constraints for any complex tool path with little computational overhead. Simulations and machining experiments are conducted to verify the effectiveness and superiorities of the proposed method.

Keywords

B-spline feedrate / Non-uniform rational B-splines (NURBS) tool path / Knot insertion / Bidirectional scanning / Computer numerical control (CNC) machining

Cite this article

Download citation ▾
Yang Li, Fu-Sheng Liang, Lei Lu, Cheng Fan. Improved time-optimal B-spline feedrate scheduling for NURBS tool paths in CNC machining. Advances in Manufacturing, 2023, 11(1): 111-129 DOI:10.1007/s40436-022-00413-1

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Piegl L, Tiller W. The NURBS book, 1997, 2 New York: Springer.

[2]

Yau HT, Kuo MJ. NURBS machining and feed rate adjustment for high-speed cutting of complex sculptured surfaces. Int J Prod Res, 2001, 39(1): 21-41.

[3]

Sun YW, Sun SX, Xu JT, et al. A unified method of generating tool path based on multiple vector fields for CNC machining of compound NURBS surfaces. Comput Aided Des, 2017, 91: 14-26.

[4]

Jafarzadeh E, Movahhedy MR, Khodaygan S, et al. Prediction of machining chatter in milling based on dynamic FEM simulations of chip formation. Adv Manuf, 2018, 6(3): 334-344.

[5]

Lyu H, Liu Y, Guo JY, et al. Tool-path generation for industrial robotic surface-based application. Adv Manuf, 2019, 7(1): 64-72.

[6]

Liang FS, Kang CW, Fang FZ. A review on tool orientation planning in multi-axis machining. Int J Prod Res, 2020, 59(18): 1-31.

[7]

Liang FS, Kang CW, Fang FZ. A smooth tool path planning method on NURBS surface based on the shortest boundary geodesic map. J Manuf Process, 2020, 58: 646-658.

[8]

Lu L, Zhang J, Fuh JYH, et al. Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces. Robot Comput Integr Manuf, 2020, 65.

[9]

Chen JP, Gu L, He GJ. A review on conventional and nonconventional machining of SiC particle-reinforced aluminium matrix composites. Adv Manuf, 2020, 8(3): 279-315.

[10]

Sang YC, Yao CL, Lv YQ, et al. An improved feedrate scheduling method for NURBS interpolation in five-axis machining. Precis Eng, 2020, 64: 70-90.

[11]

Zhao J, Xiang YC, Fan C. A new method for polishing the inner wall of a circular tube with a soft abrasive rotating jet. Powder Technol, 2021, 398.

[12]

Yang DCH, Kong T. Parametric interpolator versus linear interpolator for precision cnc machining. Comput Aided Des, 1994, 26(3): 225-234.

[13]

Yeh SS, Hsu PL. The speed-controlled interpolator for machining parametric curves. Comput Aided Des, 1999, 31(5): 349-357.

[14]

Yeh SS, Hsu PL. Adaptive-feedrate interpolation for parametric curves with a confined chord error. Comput Aided Des, 2002, 34(3): 229-237.

[15]

Farouki RT, Tsai YF, Wilson CS. Physical constraints on feedrates and feed accelerations along curved tool paths. Comput Aided Geom D, 2000, 17(4): 337-359.

[16]

Bobrow JE, Dubowsky S, Gibson JS. Time-optimal control of robotic manipulators along specified paths. Int J Robot Res, 1985, 4(3): 3-17.

[17]

Timar SD, Farouki RT, Smith TS, et al. Algorithms for time-optimal control of CNC machines along curved tool paths. Robot Comput Integr Manuf, 2005, 21(1): 37-53.

[18]

Dong J, Stori JA. A generalized time-optimal bidirectional scan algorithm for constrained feed-rate optimization. J Dyn Sys-T Asme, 2006, 128(2): 379-390.

[19]

Sun YW, Wang J, Guo DM. Guide curve based interpolation scheme of parametric curves for precision CNC machining. Int J Mach Tool Manu, 2006, 46(3/4): 235-242.

[20]

Zhang K, Yuan CM, Gao XS. Efficient algorithm for time-optimal feedrate planning and smoothing with confined chord error and acceleration. Int J Adv Manuf Technol, 2013, 66(9/12): 1685-1697.

[21]

Zhou JF, Sun YW, Guo DM. Adaptive feedrate interpolation with multiconstraints for five-axis parametric toolpath. Int J Adv Manuf Technol, 2014, 71(9/12): 1873-1882.

[22]

Barre PJ, Bearee R, Borne P, et al. Influence of a jerk controlled movement law on the vibratory behaviour of high-dynamics systems. J Intell Robot Syst, 2005, 42(3): 275-293.

[23]

Bharathi A, Dong JY. Feedrate optimization for smooth minimum-time trajectory generation with higher order constraints. Int J Adv Manuf Technol, 2016, 82(5/8): 1029-1040.

[24]

Erkorkmaz K, Altintas Y. High speed CNC system design. part I: jerk limited trajectory generation and quintic spline interpolation. Int J Mach Tool Manu, 2001, 41(9): 1323-1345.

[25]

Lin MT, Tsai MS, Yau HT. Development of a dynamics-based NURBS interpolator with real-time look-ahead algorithm. Int J Mach Tool Manu, 2007, 47(15): 2246-2262.

[26]

Tang L, Huang J, Zhu LM, et al. Path tracking of a cable-driven snake robot with a two-level motion planning method. IEEE-Asme T Mech, 2019, 24(3): 935-946.

[27]

Jahanpour J, Alizadeh MR. A novel acc-jerk-limited NURBS interpolation enhanced with an optimized S-shaped quintic feedrate scheduling scheme. Int J Adv Manuf Technol, 2014, 77(9/12): 1889-1905.

[28]

Fang Y, Qi J, Hu J, et al. An approach for jerk-continuous trajectory generation of robotic manipulators with kinematical constraints. Mech Mach Theory, 2020, 153.

[29]

Lee AC, Lin MT, Pan YR, et al. The feedrate scheduling of NURBS interpolator for CNC machine tools. Comput Aided Des, 2011, 43(6): 612-628.

[30]

Huang J, Zhu LM. Feedrate scheduling for interpolation of parametric tool path using the sine series representation of jerk profile. P I Mech Eng B-J Eng, 2016, 231(13): 2359-2371.

[31]

Alintas Y, Erkormaz K. Feedrate optimization for spline interpolation in high speed machine tools. CIRP Ann-Manuf Techn, 2003, 52(1): 297-302.

[32]

Sencer B, Altintas Y, Croft E. Feed optimization for five-axis CNC machine tools with drive constraints. Int J Mach Tool Manu, 2008, 48(7/8): 733-745.

[33]

Liu H, Liu Q, Sun PP, et al. The optimal feedrate planning on five-axis parametric tool path with geometric and kinematic constraints for CNC machine tools. Int J Prod Res, 2016, 55(13): 3715-3731.

[34]

Xie FB, Chen LF, Li ZY, et al. Path smoothing and feed rate planning for robotic curved layer additive manufacturing. Robot Comput Integr Manuf, 2020, 65.

[35]

Erkorkmaz K, Heng M. A heuristic feedrate optimization strategy for NURBS toolpaths. CIRP Ann-Manuf Techn, 2008, 57(1): 407-410.

[36]

Sun YW, Zhao Y, Bao YR, et al. A smooth curve evolution approach to the feedrate planning on five-axis toolpath with geometric and kinematic constraints. Int J Mach Tool Manu, 2015, 97: 86-97.

[37]

Liang FS, Zhao J, Ji SJ. An iterative feed rate scheduling method with confined high-order constraints in parametric interpolation. Int J Adv Manuf Technol, 2017, 92(5/8): 2001-2015.

[38]

Li GX, Liu HT, Yue W, et al. Feedrate scheduling of a five-axis hybrid robot for milling considering drive constraints. Int J Adv Manuf Technol, 2021, 112(11/12): 3117-3136.

[39]

Lu L, Zhang L, Ji S, et al. An offline predictive feedrate scheduling method for parametric interpolation considering the constraints in trajectory and drive systems. Int J Adv Manuf Technol, 2015, 83(9/12): 2143-2157.

Funding

Scientific Research Projects of Jilin Provincial Department of Education(JJKH20200104KJ)

National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809(51975392)

AI Summary AI Mindmap
PDF

186

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/