A CNN-plus-state-space-model multi-task network predicts laser weld penetration state (99.35% accuracy), depth (1.79 mm error), and cross-section morphology (95.65% accuracy) from top-view weld-pool images and welding parameters.
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A multi-task spatiotemporal deep neural network for predicting penetration depth and morphology in laser welding
A CNN-plus-state-space-model multi-task network predicts laser weld penetration state (99.35% accuracy), depth (1.79 mm error), and cross-section morphology (95.65% accuracy) from top-view weld-pool images and welding parameters.