Parameter Optimization of High Deposition Rate Laser Cladding Based on the Response Surface Method and Genetic Neural Network Model

Yifan Pang; Geyan Fu; Mingyu Wang; Yanqi Gong; Siqi Yu; Jiachao Xu; Fan Liu

doi:10.3788/CJL202148.0602112

[1] Shi Y S[M]. Laser manufacturing technology, 42-262(2012).

[2] Li D S, Shi T, Shi S H et al. Laser cladding forming technology of flat-top thin-walled part based on special-shaped base surface[J]. Chinese Journal of Lasers, 46, 1102002(2019).

[3] Ocelík V, Nenadl O, Palavra A et al. On the geometry of coating layers formed by overlap[J]. Surface and Coatings Technology, 242, 54-61(2014).

[4] Wang H M. Materials' fundamental issues of laser additive manufacturing for high-performance large metallic components[J]. Acta Aeronautica et Astronautica Sinica, 35, 2690-2698(2014).

[5] Huang J S, Shi S H, Sun C F. The existing state of rapid prototyping by large power laser accurately clading metal powder[J]. Journal of Suzhou Institute of Silk Textile Technology, 25, 16-18(2005).

[6] Li Z, Sui S, Yuan Z H et al. Microstructure and tensile properties of high-deposition-rate laser metal deposited GH4169 alloy[J]. Chinese Journal of Lasers, 46, 0102004(2019).

[7] Dong C H[M]. MATLAB neural network and application(2005).

[8] Li Y H, Liu P, Zhou J B et al. Center extraction of structured light stripe based on back propagation neural network[J]. Acta Optica Sinica, 39, 1212005(2019).

[9] Zhang M Y, Liang Y M. Color Fourier ptychography microscopy using three-dimensional convolutional neural network[J]. Acta Optica Sinica, 40, 2011001(2020).

[10] Jiang W W, Fu G Y, Zhang J P et al. Prediction of geometrical shape of coaxial wire feeding cladding in three-beam[J]. Infrared and Laser Engineering, 49, 0305005(2020).

[11] Liu L J, Jiang Y Q, Wang X P et al. Inverse solution of BP neural network for laser remelting parameters[J]. Journal of Harbin University of Science and Technology, 22, 112-116(2017).

[12] Rahimi M H, Shayganmanesh M, Noorossana R et al. Modelling and optimization of laser engraving qualitative characteristics of Al-SiC composite using response surface methodology and artificial neural networks[J]. Optics & Laser Technology, 112, 65-76(2019). http://www.sciencedirect.com/science/article/pii/S0030399217310484

[13] Yan R, Li H, Li J C et al. Process parameters optimization of polystyrene powder selective laser sintering based on response surface methodology[J]. Chinese Journal of Lasers, 46, 0302015(2019).

[14] Gong Y Q, Fu G Y, Shi T et al. Research on local atmosphere protection model of titanium alloy laser cladding in open environment[J]. Chinese Journal of Lasers, 47, 1102006(2020).

[15] Wen H J, Meng X L, Xu X C et al. Multi-objective optimization of laser cladding process parameters based on neural network and genetic algorithm[J]. Applied Laser, 39, 734-740(2019).

[16] Zhang B, Chang S, Wang J et al. Feature points extraction of laser vision weld seam based on genetic algorithm[J]. Chinese Journal of Lasers, 46, 0102001(2019).

微信扫一扫：分享

微信扫一扫：分享