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English(EN) A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks

新的AI算法用更少的标记数据预测焊接熔深 · 跟踪2个来源

作者 PulseAugur 编辑部 · [4 个来源] ·

研究人员开发了新的焊接熔深状态预测算法，解决了传统监督式深度学习方法的局限性。一种方法利用无监督域自适应和渐进式源域扩展策略，以提高模型在TIG和激光焊接等不同焊接过程中的性能。另一种方法采用物理信息神经网络和少样本学习的自监督学习，使用最少的标记数据在激光焊接熔深预测中实现高精度。 AI

影响 这些方法可以显著减少工业焊接应用中对大量标记数据的需求，为更高效、更自动化的质量控制铺平道路。

排序理由 两篇arXiv论文详细介绍了用于焊接熔深预测的新型算法。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →

新的AI算法用更少的标记数据预测焊接熔深 · 跟踪2个来源

报道来源 [4]

  1. arXiv cs.AI TIER_1 English(EN) · Xinhua Tang ·

    A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG welding

    Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under domain shift, such as when transferring models between welding processes with distinct physical mechanisms:for instance, from arc-d…

  2. arXiv cs.AI TIER_1 English(EN) · Haichao Cui ·

    A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks

    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 penetration state is therefore essential for ensuring weld quality. To this end, this paper introduces…

  3. arXiv cs.CV TIER_1 English(EN) · Sen Li, Xiaoying Liu, Xiaojian Xu, Chendong Shao, Yaqi Wang, Ling Lan, Xinhua Tang, Haichao Cui ·

    A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks

    arXiv:2606.26059v1 Announce Type: new Abstract: 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 penetration state is therefore essential for ensuring …

  4. arXiv cs.CV TIER_1 English(EN) · Sen Li, Haichao Cui, Chendong Shao, Yaqi Wang, Xinhua Tang ·

    A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG welding

    arXiv:2606.26078v1 Announce Type: new Abstract: Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under domain shift, such as when transferring models between welding processes with disti…

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