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摘要:Resistance spot welding(RSW) plays an important role in manufacturing.The quality of the welding can be efficiently assessed by its appearance.Image segmentation is an important part of the RSW appearance inspection.However,the classical image segmentation algorithms cannot work very well because of the various RSW appearances.In this study,a novel inspection method is proposed based on semantic segmentation.We choose MobileNetV2 as the backbone for the semantic segmentation.After modification and optimization of the network,our model achieves an accuracy of 89% mean intersection-ofunion(mIOU),which is averagely 30% higher than the classical image segmentation algorithms.A classifier further evaluates the quality of the RSW according to some geometric features of the segmented regions,and the classification accuracy is improved by 0.79%.This research is of great importance for the high accuracy quality control of the massive production to reduce the producing cost and improve the efficiency of the RSW pipeline.
会议名称:

2019 2nd International Conference on Communication,Network and Artificial Intelligence(CNAI 2019)

会议时间:

2019-12-27

会议地点:

中国广东广州

  • 专辑:

    工程科技Ⅰ辑; 信息科技

  • 专题:

    金属学及金属工艺; 计算机软件及计算机应用

  • DOI:

    10.26914/c.cnkihy.2019.057631

  • 分类号:

    TG453.9;TP391.41

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