Monitoring of high-speed laser welding process based on vapor plume

Abstract

The increase of welding speed can improve the productivity of laser welding. The behavior of vapor plume is an important indicator reflecting the state of the laser welding process. However, the behavior of vapor plume in high-speed laser welding (whose welding speed is higher than 10 m/min) has not been studied adequately. In this research, images of the vapor plume in high-speed laser welding of SUS304 austenitic stainless steel are captured through high-speed imaging for the monitoring of the welding process. Characteristics of the vapor plume are extracted with image processing, and the influences of laser power and welding speed on these characteristics are analyzed. The relationships between the behavior of vapor plume and melt pool are discussed, and three ejection regimes of the vapor plume are proposed. In order to predict the occurrence of humping, which is a typical defect in high-speed laser welding, samples are built by applying a time sliding window and then a classification model is built with the random forest. In addition, the importance of features in the classification is analyzed. The test results show that the proposed method can predict the humping defect in high-speed laser welding accurately.