3 citations · 4 across the 4 of their papers we have counts for
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A multi-task spatiotemporal deep neural network for predicting penetration depth and morphology in laser welding
Sen Li, Haichao Cui, Chendong Shao +2
In laser penetration welding, the assessment of penetration state and weld seam morphology plays a crucial role in determining the weld quality. This paper presents a comprehensive…
A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG welding
Sen Li, Haichao Cui, Chendong Shao +2
Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under domain shift, such as when tran…
A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks
Sen Li, Xiaoying Liu, Xiaojian Xu +5
The laser welding full-penetration is of critical importance, as it constitutes one of the fundamental factors in achieving defect-free welded joints. Accurate prediction of the pe…
Physics-Guided Spatiotemporal State Space Modeling for Lookahead Molten Pool Segmentation in Laser Wire-Feed Welding
Sen Li, Haichao Cui, Changhao Yin +4
Real-time weld-pool perception is critical for closed-loop control in laser wire-feed welding, where sensing, computation, and actuator response introduce unavoidable delay. This p…