Abstract
Spatter formation is still an issue in welding, particularly in laser welding. This research takes up the topic and proposes a machine vision approach for spatter tracking in high speed image series. After a description of the multi hypothesis tracking method, in which a Kalman-filter is used for optimal object state estimation, the tracking is applied on high speed images from an experimental series on laser welding with beam oscillation using stainless steel. On the basis of its results three different spatter formation mechanisms could be identified and described. Those were spatter formation by material ablation, by periodic re-entry of the laser spot into the melt pool and by melt pool dynamics.
Original language | English |
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Pages (from-to) | 35-42 |
Number of pages | 8 |
Journal | CIRP Journal of Manufacturing Science and Technology |
Volume | 14 |
DOIs | |
State | Published - 1 Aug 2016 |
Keywords
- Beam oscillation
- Kalman filter
- Laser welding
- Machine vision
- Multi hypothesis tracking
- Spatter