Open AccessOn-line monitoring of penetration state in laser-arc hybrid welding based on keyhole and arc features
Author(s) -
Minghai Zhang,
Leshi Shu,
Qi Zhou,
Ping Jiang,
Zhaoliang Gong
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1884/1/012039
Subject(s) - keyhole , welding , penetration (warfare) , arc (geometry) , laser beam welding , laser , penetration depth , plasma arc welding , materials science , arc blow , arc lamp , arc welding , weld pool , computer science , gas metal arc welding , computer vision , mechanical engineering , gas tungsten arc welding , optics , engineering , metallurgy , physics , operations research
Incomplete penetration is a typical defect in laser-arc hybrid welding. On-line monitoring of welding process is an important method to assess welding quality. In laser-arc hybrid welding, there is a strong correlation between keyhole, arc and incomplete penetration. Therefore, an on-line monitoring method of penetration state based on keyhole and arc features is proposed in this paper. In the proposed method, the images of keyhole and arc in laser-arc hybrid welding are captured by high-speed camera, and then the keyhole and arc features are extracted by image processing algorithm. Finally, the features are used as input to classify the penetration state using SVM model. The results show that the SVM model based on keyhole and arc features can accurately identify the penetration state.