Prediction of characteristic and performance of laser cladding for Al alloy based on artificial neural network

被引：0

作者：

Department of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China ^{[1
]}

机构：

[1] Department of Materials Science and Engineering, Huazhong University of Science and Technology

来源：

Zhongguo Jiguang/Chinese Journal of Lasers | 2008年 / 35卷 / 10期

关键词：

Aluminum alloy; Artificial neural network; Cladding layer; Laser cladding; Laser technique;

D O I：

10.3788/cjl20083510.1632

中图分类号：

学科分类号：

摘要：

Based on the artificial neural network (ANN), a model is established to describe the laser cladding parameters and the characteristic and performance of laser cladding layers. The characteristic and performance of laser cladding layers are predicted with the model in which the input parameters consist of laser power, scanning velocity, laser spot diameter, and coating proportion and the output parameters include the clad hardness, the clad width, and the clad height. The results show that the mean error is small, and the model has good verifying precision and excellent ability of predicting. The model can basically forecast the characteristic and performance of laser cladding layers.

引用

页码：1632 / 1636

页数：4

共 11 条

[1]

Zuo T., Laser Materials Processing of High Strength Aluminum Alloy, (2002)

[2]

Huang K., Lin X., Chen C., Et al., Microstructure and wear behaviour of laser-clad Zr-Cu-Ni-Al/TiC composites on AZ91D magnesium alloy, Chinese J. Lasers, 34, 4, pp. 449-554, (2007)

[3]

Liu H., Wang C., Gao Y., Et al., Laser cladding amorphous composite coating of Cu-Zr-Al on magnesium alloy surface, Chinese J. Lasers, 33, 5, pp. 709-713, (2006)

[4]

Niu X., Chao M., Wang W., Et al., In situ synthesized NbC particulate reinforced Ni-based composite coatings by laser cladding, Chinese J. Lasers, 33, 7, pp. 987-992, (2006)

[5]

Liu R., Ji Z., Microscopic morphology and microstructure of phases between dilution zone and clad zone in laser remelting NiCrBSi/TiN layer, Chinese J. Lasers, 34, 9, pp. 1292-1296, (2007)

[6]

Toyserkani E., Khajepour A., Corbin S., Laser Cladding, (2005)

[7]

Li J., Yan C., Wu J., Prospect of ANN in materials science and engineering, China Ceramic Industry, 10, 4, pp. 36-38, (2003)

[8]

Ding Z., Zheng Q., Tong X., Et al., Optimizing of laser cladding parameters of Co-based hard alloy coating based on artificial neural networks, J. Optoelectronics · Laser, 15, 3, pp. 353-355, (2004)

[9]

Wang D., Controlling laser surface strengthening artificial neural network, Laser Technology, 27, 4, pp. 317-320, (2003)

[10]

Xu D., Zhou J., Guo H., Application for laser cladding forming using evolutionary neural networks, Applied Laser, 26, 5, pp. 303-306, (2006)

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