Chinese Journal of Lasers, Volume. 48, Issue 6, 0602112(2021)
Parameter Optimization of High Deposition Rate Laser Cladding Based on the Response Surface Method and Genetic Neural Network Model
Fig. 4. Microstructure of laser cladding Fe314 with different deposition rates. (a) Sample 1; (b) sample 9
Fig. 7. Interactive influence of process parameters on deposition rate. (a) Powder feeding velocity and power; (b) defocus and power; (c) scanning velocity and powder feeding velocity
Fig. 9. Diagrams of error iteration. (a) Evolution of genetic fitness; (b) iteration of neural network error
Fig. 10. Predicted comparison results of RSM and GA-BP models. (a) Model of RSM; (b) model of GA-BP
|
|
|
|
Get Citation
Copy Citation Text
Yifan Pang, Geyan Fu, Mingyu Wang, Yanqi Gong, Siqi Yu, Jiachao Xu, Fan Liu. Parameter Optimization of High Deposition Rate Laser Cladding Based on the Response Surface Method and Genetic Neural Network Model[J]. Chinese Journal of Lasers, 2021, 48(6): 0602112
Category: Laser Material Processing
Received: Jun. 22, 2020
Accepted: Sep. 24, 2020
Published Online: Mar. 15, 2021
The Author Email: Fu Geyan (fugeyan@suda.edu.cn)