| About this Abstract |
| Meeting |
2023 AWS Professional Program
|
| Symposium
|
2023 AWS Professional Program
|
| Presentation Title |
Monitoring Torch Position and Weld Quality with Reversed Electrode Image during GTAW Process |
| Author(s) |
Zongyao Chen, Yu Fu, Zhili Feng, Jian Chen, Shanben Chen |
| On-Site Speaker (Planned) |
Zongyao Chen |
| Abstract Scope |
Weld torch position and attitude (TPA) relative to the weld pool surface affects the quality of the weld, which are also the basis of control and offline programming of the arc welding process. The reversed electrode image (REI) can be observed on the weld pool surface during the GTAW welding process through the high-speed camera. This information can be used to monitor weld pool surface geometry and weld quality. This research developed a new method to monitor (TPA) attitude relative to the weld pool surface based on REI by considering the weld pool surface as a spherical mirror. The deviation distance and deflection angle of the welding torch relative to the correct position and attitude can be calculated based on the measurement of the distance between the REI and electrode in the passive vision image of the weld pool, arc length, and weld pool geometry. The REI-TPA model was verified with bead-on-plate welding experiments on S304 stainless steel plate, contours of REI and electrode as well as the weld pool geometry was extracted from the weld pool image with a robust AI algorithm. |
| Proceedings Inclusion? |
Undecided |