数控加工进给速度参数优化研究现状与展望

doi:10.7527/S1000-6893.2021.25467

Abstract

Abstract: Feedrate optimization is an most important link in the realization of Computer Numerical Control(CNC) intelligent machining, and is also a key issue that needs to be solved urgently in the field of intelligent manufacturing in the future. In this paper, three optimization methods are discussed, which are off-line feedrate optimization with the goal of machining efficiency, machining quality, machine stability and constant cutting force, on-line adaptive feedrate optimization with constant cutting force and cutting power, and the integration of the two method. The current research status and theoretical achievements at home and abroad are summarized. The application effects, advantages and disadvantages of various optimization methods are reviewed. Then, several representative breakthrough research directions and future development trends are proposed for intelligent optimization of process parameters. We expect to better realize the independent decision-making and intelligent optimization of the CNC system, improve the processing efficiency and quality, improve the application performance of the CNC system, and promote the independent development and intelligent manufacturing.

Key words: CNC machining, feedrate, parameter optimization, adaptive control, intelligent optimization algorithm

CLC Number:

V261.2

WU Baohai, ZHANG Yang, ZHENG Zhiyang, ZHANG Ying, ZHANG Siqi. Review and prospects of feedrate optimization in CNC machining[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(4): 525467-525467.

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Review and prospects of feedrate optimization in CNC machining

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[3]	Kai NING, Baolin WU. Event-triggered-based orbit maintenance control for spacecraft subsatellite point control [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(10): 329412-329412.
[4]	Leyan FANG, Han MENG, Mingzhe HOU. Iterative learning sliding mode control with precise parameter estimation and its application [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(1): 628889-628889.
[5]	Guangquan DUAN, Guoping LIU. Adaptive prescribed control of position and attitude of combined spacecraft based on fully actuated system approach [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(1): 628837-628837.
[6]	Xiaoyun SUN, Shufan WU, Qiang SHEN. LMI-based output tracking robust drag-free control with model reference adaptive scheme [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S1): 727654-727654.
[7]	Runchang HU, Zian WANG, Yongliang CHEN, Dapeng ZHOU, Dapeng YANG, Zheng GONG. Stability augmentation control of thrust-vectored V/STOL aircraft based on L1 adaptive control [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S1): 727642-727642.
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[11]	Baohui JIA, Fan JIANG, Yuxin WANG, Du WANG. Fault diagnosis method based on civil aircraft maintenance text data [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(5): 326598-326598.
[12]	Feiyan GUO, Jianhua LIU, Qingdong XIAO, Shihong XIAO, Zhongqi WANG. Monitoring and evaluation of working condition and adaptive control technology for digital assembly tooling [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(16): 427914-427914.
[13]	Yuhang XIA, Yu WANG. Comparative study on optimal control methods of independent excitation DC power generation system [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(16): 327975-327975.
[14]	YANG Xiaowei, GE Yaowen, DENG Wenxiang, YAO Jianyong, ZHOU Ning. Active fault-tolerant control for hydraulic actuating cylinders of aeroengine guide vane control mechanisms [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 625464-625464.
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