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

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.