Product Code: ICAL06_705

Using Machine Vision for Observation of Phenomena during Laser Hybrid Welding
Authors:
Anna Fellman, LUT; Lappeenranta Finland
Antti Salminen, Lappeenranta University of Technology, Department of Mechanical Engineering, Laser processing laboratory; Lappeenranta Finland
Henri Fennander, Lappeenranta University of Technology, Department of Information Technology, Machine Vision and Pattern recognition research group; Lappeenranta Finland
Ville Kyrki, Lappeenranta University of Technology, Department of Information Technology, Machine Vision and Pattern recognition research group; Lappeenranta Finland
Presented at ICALEO 2006

Laser hybrid welding process is today a widely studied welding process. Many research groups are trying to figure the phenomenon during the process. A lot of those occurring during laser hybrid welding process can be observed with the help of high speed videography. The high speed of the droplet formation and their movement to the melt pool, are setting requirements to the frequency of the videography in order to get reliable information about the process. Because of large number of pictures resulting from the high photography frequency (over 1000 Hz), it is time-consuming and frustrating to use only the human eyes for observation of changes in process. In some cases it is possible to use machine vision for the observation of certain characters. The machine vision system was used to study videos of CO2 laser-MAG hybrid welding experiments in which welding parameters were changed one at a time. The quality of the welds was observed by visual and macrographic examination. In the study the regularity of pulse frequency of the arc and direction of droplet flight were measured with the help of machine vision. Due to stable nature of keyhole welding part of the process, these characters show the stability of the welding process. It was seen that the automatic observation can be used if the quality of the picture is good enough and if the illumination effect of the process is low enough to be able see the characters with good enough reliability. From those videos in which it was possible to use the machine vision, it was seen that the parameters have an effect on the stability of pulsing frequency and the direction of droplet movement. The use of automatic observation of changes in process is a valuable tool for process optimization. The gathered information can be utilized in achieving an optimized process giving the best possible productivity.