Imager-Based Techniques for Analyzing Metallic Melt Pools for Additive Manufacturing
Presented is a vision-based algorithm for extracting physical properties from melt pools. The bandwidth requirements for traditional high speed video are too high for real time analysis so silicon retinas are used. This method of imaging has a very fine temporal resolution, high dynamic range, and low bandwidth requirements. The ability to monitor melt pools in real time would improve the quality of laser printed parts and welds because it would allow automatic control systems to recognize and correct imperfections during the printing and welding processes. By measuring the change of intensity within a melt pool then applying blind source separation techniques, spatiotemporal data can be extracted. First a circular membrane model is evaluated to validate the technique. Then the separation technique is performed with a traditional camera on gallium pools of different depths and various lighting conditions. Finally, silicon retina data is used to show that the technique can be applied for this type of imager.
KeywordsAdditive manufacturing Event-based imaging Melt pool depth Blind source separation Modal analysis
This work was completed as a part of the 2018 Los Alamos National Laboratory Dynamic Summer School. Los Alamos National Laboratory is operated by Los Alamos National Security LLC, for the National Nuclear Security Administration of the U.S. Department of Energy, under DOE Contract DE-AC52-06NA25396.
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