Laser & Optoelectronics Progress, Volume. 59, Issue 2, 0214001(2022)
A Configurable BP Neural Network Accelerator for Laser Welding Parameter Calculation
[1] Wang D C. Controlling laser surface strengthening process based on artificial neural network[J]. Laser Technology, 27, 317-320(2003).
[2] Guo L, Wang S H, Zhang Q M et al. Optimization of fiber laser welding process viarables and performance prediction based on BP neural network[J]. Applied Laser, 30, 479-482(2010).
[9] Pan L J, Chen W F, Cui R F et al. Quantitative analysis of aluminum alloy based on laser-induced breakdown spectroscopy and radial basis function neural network[J]. Laser & Optoelectronics Progress, 57, 193002(2020).
[13] Hu J, Liu Y D, Sun X D et al. Quantitative determination of benzoic acid in flour based on terahertz time-domain spectroscopy and BPNN model[J]. Laser & Optoelectronics Progress, 57, 073002(2020).
[16] Hu Y, Li Z H, Lü T. Quantitative measurement of iron content in geological standard samples by laser-induced breakdown spectroscopy combined with artificial neural network[J]. Laser & Optoelectronics Progress, 54, 053003(2017).
[17] Shi Z F, Ye P, Sun C et al. Object detection algorithm applied to optical genetic laser projection system[J]. Laser & Optoelectronics Progress, 57, 061503(2020).
[18] Zhou D W, Qiao X J, Zhang L J et al. Parameters optimization of laser welding process of galvanized steel and 6016 aluminum alloy based on BP neural network and its microstructure and mechanical properties[J]. The Chinese Journal of Nonferrous Metals, 24, 678-688(2014).
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Boyu Fan, Zaifeng Shi, Zhe Wang, Shaoxiong Li, Tao Luo. A Configurable BP Neural Network Accelerator for Laser Welding Parameter Calculation[J]. Laser & Optoelectronics Progress, 2022, 59(2): 0214001
Category: Lasers and Laser Optics
Received: Jan. 29, 2021
Accepted: Mar. 9, 2021
Published Online: Dec. 23, 2021
The Author Email: Boyu Fan (fanboyu@tju.edu.cn), Zaifeng Shi (shizaifeng@tju.edu.cn)