Adaptive edge detection of molten pool based on coarse-grained regularization in restricted solution space

LIU Tianyuan; BAO Jinsong; WANG Junliang; ZHENG Xiaohu; WANG Jiacheng

doi:10.12073/j.hjxb.20200815002

TRANSACTIONS OF THE CHINA WELDING INSTITUTION > 2020 > 41(12): 49-54. > DOI: 10.12073/j.hjxb.20200815002

LIU Tianyuan, BAO Jinsong, WANG Junliang, ZHENG Xiaohu, WANG Jiacheng. Adaptive edge detection of molten pool based on coarse-grained regularization in restricted solution space[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(12): 49-54. DOI: 10.12073/j.hjxb.20200815002

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Adaptive edge detection of molten pool based on coarse-grained regularization in restricted solution space

College of Mechanical Engineering, Donghua University, Shanghai 201600, China

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Received Date: August 14, 2020
Available Online: December 27, 2020

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Abstract

Abstract

Edge detection is a key step in the image processing of the molten pool. In view of the sharp changes in the arc in the molten pool area, the edge detection method that relies on artificially setting the threshold is difficult to adapt to the dynamic change of the arc. This paper proposes a deep learning-based edge extraction mode of the molten pool. Firstly, pixel-level annotation and data augmentation are performed on the original molten pool image to build a dataset. Secondly, a coarse-grained regularization method in restricted solution space (CGRRSS) is proposed to enhance edge features. Finally, the proposed method is compared with the traditional methods in both quantitative and qualitative aspects. The results show that the proposed method has a higher recall of edge points, the obtained molten pool edge is more continuous and has a better suppression effect on false edges. The detection time of a single image is 6.2 ms, which can meet the needs of online monitoring.
- molten pool image,
- deep learning,
- edge detection,
- regularization,
- coarse-grained

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References

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Adaptive edge detection of molten pool based on coarse-grained regularization in restricted solution space