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ARTICLE

Optimization of CNC Turning Machining Parameters Based on Bp-DWMOPSO Algorithm

Jiang Li, Jiutao Zhao, Qinhui Liu*, Laizheng Zhu, Jinyi Guo, Weijiu Zhang

College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, China

* Corresponding Author: Qinhui Liu. Email: email

Computers, Materials & Continua 2023, 77(1), 223-244. https://doi.org/10.32604/cmc.2023.042429

Abstract

Cutting parameters have a significant impact on the machining effect. In order to reduce the machining time and improve the machining quality, this paper proposes an optimization algorithm based on Bp neural network-Improved Multi-Objective Particle Swarm (Bp-DWMOPSO). Firstly, this paper analyzes the existing problems in the traditional multi-objective particle swarm algorithm. Secondly, the Bp neural network model and the dynamic weight multi-objective particle swarm algorithm model are established. Finally, the Bp-DWMOPSO algorithm is designed based on the established models. In order to verify the effectiveness of the algorithm, this paper obtains the required data through equal probability orthogonal experiments on a typical Computer Numerical Control (CNC) turning machining case and uses the Bp-DWMOPSO algorithm for optimization. The experimental results show that the Cutting speed is 69.4 mm/min, the Feed speed is 0.05 mm/r, and the Depth of cut is 0.5 mm. The results show that the Bp-DWMOPSO algorithm can find the cutting parameters with a higher material removal rate and lower spindle load while ensuring the machining quality. This method provides a new idea for the optimization of turning machining parameters.

Keywords

Machining parameters; Bp neural network; Multiple Objective Particle Swarm Optimization; Bp-DWMOPSO algorithm

Cite This Article

APA Style
Li, J., Zhao, J., Liu, Q., Zhu, L., Guo, J. et al. (2023). Optimization of CNC Turning Machining Parameters Based on Bp-DWMOPSO Algorithm. Computers, Materials & Continua, 77(1), 223–244. https://doi.org/10.32604/cmc.2023.042429
Vancouver Style
Li J, Zhao J, Liu Q, Zhu L, Guo J, Zhang W. Optimization of CNC Turning Machining Parameters Based on Bp-DWMOPSO Algorithm. Comput Mater Contin. 2023;77(1):223–244. https://doi.org/10.32604/cmc.2023.042429
IEEE Style
J. Li, J. Zhao, Q. Liu, L. Zhu, J. Guo, and W. Zhang, “Optimization of CNC Turning Machining Parameters Based on Bp-DWMOPSO Algorithm,” Comput. Mater. Contin., vol. 77, no. 1, pp. 223–244, 2023. https://doi.org/10.32604/cmc.2023.042429



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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