Prediction of molten pool width with artificial neural network model

被引：1

作者：

Wang, Teng ^{[1
]}

Gao, Xiangdong ^{[1
]}

机构：

[1] Guangdong Univ Technol, Fac Electromech Engn, Guangzhou 510090, Guangdong, Peoples R China

来源：

ADVANCED COMPOSITE MATERIALS, PTS 1-3 | 2012年 / 482-484卷

关键词：

disk laser welding; molten pool width; prediction; BP neural network; QUALITY;

D O I：

10.4028/www.scientific.net/AMR.482-484.2210

中图分类号：

TB33 [复合材料];

学科分类号：

摘要：

Online monitoring of welding process has become necessary as the use of laser welding increases. In laser welding the molten pool width is one of the most important quality aspects. Metal plume and spatters are measured and used as signals for predicting the molten pool width. In this work, BP neural network model is established. The effectiveness of the model is demonstrated, the results show good agreements with corresponding experimental data.

引用

页码：2210 / 2213

页数：4

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