Defect Detection of Welding Spots on Steel Plate Surface Based on Improved Resnet Feature Extraction

Kang Sun; Shuchun Dong

doi:10.23977/autml.2022.030303

Defect Detection of Welding Spots on Steel Plate Surface Based on Improved Resnet Feature Extraction

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DOI: 10.23977/autml.2022.030303 | Downloads: 5 | Views: 423

Author(s)

Kang Sun ¹, Shuchun Dong ¹

Affiliation(s)

¹ Dianrong Intelligent Technology Co., Ltd., Kunshan, 215334, China

Corresponding Author

Kang Sun

ABSTRACT

In order to deal with the problem of defect detection of welding spot on steel plate surface, an improved ResNet feature extraction method is proposed by embedding Squeeze and Excitation (SE) module, then the XGBoost classifier is combined to achieve reliable welding spot defect detection. The experimental results show that the proposed algorithm has achieved remarkable improvement in main indexes such as accuracy, precision and F1 score, the recall rate reaches 97%, which is of great significance for further industrial applications.

KEYWORDS

Welding spots, Detection of defects, ResNet, SE Module, Feature extraction

CITE THIS PAPER

Kang Sun, Shuchun Dong, Defect Detection of Welding Spots on Steel Plate Surface Based on Improved Resnet Feature Extraction. Automation and Machine Learning (2022) Vol. 3: 13-18. DOI: http://dx.doi.org/10.23977/autml.2022.030303.

REFERENCES

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Defect Detection of Welding Spots on Steel Plate Surface Based on Improved Resnet Feature Extraction

Author(s)

Affiliation(s)

Corresponding Author

ABSTRACT

KEYWORDS

CITE THIS PAPER

REFERENCES

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