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A High-Flexible ACC/DEC Look-Ahead Strategy Based on Quintic Bézier Feed Rate Curve

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9834))

Abstract

To realize real-time generation of a feed rate profile during NC machining process, the look-ahead strategy utilizing bidirectional scanning algorithm is widely adopted. However, the strategy is time-consuming since the acceleration/deceleration \((\mathrm{{ACC/DEC}})\) scheduling is called frequently. To overcome the deficiency, a high-flexible ACC/DEC look-ahead strategy is proposed in this paper, which is composed of a ACC/DEC scheduling and a backward scanning and forward revision (BSFR) algorithm. Firstly, the ACC/DEC scheduling based on quintic Bézier curve is presented, and a total of 20 types of feed rate profiles are deduced. The scheduling has the characteristics of jerk continuity, simple calculation, and ease of implementation. After that, to deduce the number of times that the ACC/DEC scheduling is called, the BSFR algorithm is put forward. Meanwhile, constraints such as machine’s kinematics, chord error, and command feed rate are also taken into account. Experiments are performed at last. Not only is the optimum feed rate profile generated in real time, but also it has nearly \(40\,\%\) decrement on the number of calls of scheduling, which demonstrates the proposed strategy is valid and feasible in NC machining.

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Acknowledgements

This research was supported in part by National Key Basic Research Program of China under Grant 2013CB035804, National Natural Science Foundation of China under Grant U1201244, and China Postdoctoral Science Foundation under Grant 2015M80325.

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Correspondence to Zhenhua Xiong .

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Appendix

Appendix

See Table 1

Table 1. The data of the time series and the formula for the maximal actual feed rate for each type

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Wang, H., Liu, C., Wu, J., Sheng, X., Xiong, Z. (2016). A High-Flexible ACC/DEC Look-Ahead Strategy Based on Quintic Bézier Feed Rate Curve. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9834. Springer, Cham. https://doi.org/10.1007/978-3-319-43506-0_60

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  • DOI: https://doi.org/10.1007/978-3-319-43506-0_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43505-3

  • Online ISBN: 978-3-319-43506-0

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