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Develop a high-precision, non-contact detection technology capable of accurately characterizing the complex micro-gap 3D morphology of weld seams in challenging-to-weld materials and critical components. Establish a multi-source, heterogeneous, multi-band signal fusion sensing approach that integrates information from the weld pool and metal vapor during the welding process. Furthermore, achieve breakthroughs in the rapid, coordinated control of laser energy and material dynamics throughout welding, providing an integrated, intelligent solution that ensures comprehensive shape and property control for large-scale welding of complex components or long-range weld seam applications.
Multi-functional Laser Welding
Multi-degree-of-freedom systems capable of conducting welding experiments on complex joint types, such as shafts, plates, busbars, and motor stators. Optional configurations include 2D vision systems, 3D vision systems, 2D/3D visual data alignment systems, and specialized weld seam recognition systems. Optional integration of automatic visual inspection combined with automated welding systems, customizable to meet specific application needs.
Intelligent Optimization During Welding
Using the ray-tracing method for finite element calculations of copper laser welding, combined with experimental observations, we obtained temperature field and melt volume data for copper weld spots under various conditions, including different defocus amounts, assembly gaps, and height differences. Additionally, leveraging the flat-wire motor laser welding test setup and a high-speed photography platform, we acquired data on large-particle spatter. Finally, we constructed a dataset correlating the assembly state of flat copper wires with optimized laser welding parameters, and developed a mapping model—based on machine learning algorithms—to predict weld bead formation and spatter behavior.
Laser Welding Integrated Solution
Targeting difficult-to-weld materials and critical components, this project develops a high-precision, non-contact detection technology capable of accurately characterizing the complex three-dimensional micro-gap morphology of weld seams. It also establishes a multi-source, heterogeneous, multi-band signal fusion approach for real-time sensing of the weld pool and metal vapor during the welding process. Furthermore, the research aims to break through advanced techniques for rapid, coordinated control of laser energy and material interaction in welding, ultimately providing an integrated, intelligent solution that ensures comprehensive process control over both the geometry and properties of large-scale welding of complex components or long-length welds.
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