Wobble-welding of copper and aluminum alloys with inline coherent imaging
Bibliographic record
Abstract
Laser welding of non-ferrous alloys for industrial applications is expanding rapidly. This trend is driven in part by the expected surge in electric vehicle market growth (requiring increased production capacity for batteries and electrical drive components), as well as continued efforts to reduce weight in construction of conventional automobiles. Increasing laser uptake for aerospace welding is also a factor. Two families of alloy that are critical to these industry sectors (aluminum and copper) present considerable challenges when approached using conventional laser welding techniques. The low absorption of near-IR industrial laser wavelengths by these alloys resists initial formation of a keyhole—a necessity for efficient coupling of energy into the workpiece. Once a keyhole is established, the low viscosity of the melt when compared with ferrous alloys results in reduced process stability and higher probability of defects. The best solution for consistent keyhole formation and defect prevention is a combination of high-brightness fiber laser sources (single-mode/low-mode) with beam wobbling. This combination has been shown to improve weldability, produce more stable and repeatable results, while broadening the process window to more-industry friendly regimes. For ease of process optimization with the wobbling technique, and for more reliable quality assurance in production, industry is turning to the direct, geometrical keyhole measurements offered by Inline Coherent Imaging (ICI). In this paper, we present an ICI investigation of beam wobbling in copper and aluminum using the latest scanner-enabled beam delivery equipment. Keyhole depth mapping within the wobble pattern demonstrates periodic, position-dependent fluctuations in the keyhole, that are not always observable in the finished weld. Keyhole and melt pool dynamics are examined for both ‘revolving’ and ‘common keyhole’ wobble welding conditions. The effects of circular wobble patterns on keyhole depth and stability are explored. These measurements provide a unique window into the dynamics of welding processes that utilize dynamic beam deflection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".