Laser Journal, Volume. 46, Issue 2, 218(2025)
Prediction method of laser bevel cutting roughness for 50 mm-thick Q235 carbon steel with 40 kW based on PSO-RBF
[6] [6] Yilbas B S, Karatas C, Uslan I, et al. Wedge cutting of mild steel by CO2 laser and cut-quality assessment in relation to normal cutting[J]. Optics and Lasers in Engineering, 2008, 46(10): 777-784.
[7] [7] Quintana G, Garcia - Romeu M L, Ciurana J. Surface roughness monitoring application based on artificial neural networks for ball-end milling operations[J]. Journal of Intelligent Manufacturing, 2011, 22: 607-617.
[8] [8] Ding H, Wang Z, Guo Y. Multi-objective optimization of fiber laser cutting based on generalized regression neural network and non-dominated sorting genetic algorithm[J]. Infrared Physics & Technology, 2020, 108: 103337.
[16] [16] Vagheesan S, Govindarajalu J. Hybrid neural network-particle swarm optimization algorithm and neural network-genetic algorithm for the optimization of quality characteristics during CO2 laser cutting of aluminum alloy[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2019, 41(8): 328.
[19] [19] Niu B, Chen J, Liu F. Optimization on the fiber laser micro-cutting of thin stainless steel sheet by artificial neural networks[J]. Advanced Science Letters, 2011, 4(3): 810-813.
Get Citation
Copy Citation Text
LI Tianhao, CHENG Wei, LI Fengxi, WANG Wentao, XU Zifa, LYU Lei. Prediction method of laser bevel cutting roughness for 50 mm-thick Q235 carbon steel with 40 kW based on PSO-RBF[J]. Laser Journal, 2025, 46(2): 218
Category:
Received: Aug. 12, 2024
Accepted: Jun. 12, 2025
Published Online: Jun. 12, 2025
The Author Email: CHENG Wei (chengweijob@163.com)