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  • https://doi.org/10.1109/mrai65197.2025.11135565Copy DOI Icon

Tungsten Electrode Abrasion Length Detection Based on Semantic Segmentation and Tip Restoration

  • Jun 19, 2025
  • Zhan Zhao +5 more
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Abstract

In tungsten inert gas welding, the tungsten electrode plays a crucial role in guiding current and transmitting electrical energy. However, the tungsten electrode is susceptible to abrasion during welding. Accurately obtaining the abrasion length of the tungsten electrode is of great significance for further optimizing the tungsten electrode replacement cycle and improving welding quality and efficiency. This paper proposes a novel detection method for the abrasion length of welding tungsten electrodes based on semantic segmentation and tip restoration. This method first uses the DeepLabV3+ model for semantic segmentation to obtain the masks of the tungsten electrode column and tip; then, based on these masks, it performs angle correction and restoration of the tungsten electrode tip; finally, by comparing the masks of the tungsten electrode tip before and after restoration, the abrasion length of the tungsten electrode is obtained. Experimental results show that this method can accurately obtain the abrasion length of the welding tungsten electrode, providing precise and objective data on the abrasion state of the tungsten electrode for welding equipment.

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