Real-time monitoring of high-power disk laser welding based on support vector machine

被引：39

作者：

Chen, Juequan ^{[1
]}

Wang, Teng ^{[1
]}

Gao, Xiangdong ^{[2
]}

Li, Wei ^{[3
]}

机构：

[1] South China Normal Univ, Sch Comp, Guangzhou 510631, Guangdong, Peoples R China

[2] Guangdong Univ Technol, Sch Electromech Engn, Guangzhou 510090, Guangdong, Peoples R China

[3] South China Normal Univ, Sch Phys & Telecommun Engn, Guangzhou 510631, Guangdong, Peoples R China

来源：

COMPUTERS IN INDUSTRY | 2018年 / 94卷

基金：

中国国家自然科学基金;

关键词：

Laser welding; Support vector machine; Real-time monitoring; Feature selection; Welding quality; SYSTEM; CLASSIFICATION;

D O I：

10.1016/j.compind.2017.10.003

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, an efficient quality monitoring system for monitoring high-power disk laser welding in real time was developed. Fifteen features of laser-induced metal vapor plume and spatters were extracted and support vector machine was adopted to establish a classifier to evaluate the welding quality. Feature selection method was employed to choose suitable features. The experiment results demonstrated that this method had satisfactory performance and could be applied to real-time monitoring application. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：75 / 81

页数：7

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