Stability detection of melt pool in laser cladding based on enhanced mask R-CNN

Linhang Li; Zhenying Xu; Yucheng Tao; Qinghua Liu; Yuxuan Zhang

doi:10.1117/12.2617296

19 November 2021 Stability detection of melt pool in laser cladding based on enhanced mask R-CNN

Linhang Li, Zhenying Xu, Yucheng Tao, Qinghua Liu, Yuxuan Zhang

Proceedings Volume 12059, Tenth International Symposium on Precision Mechanical Measurements; 120591Z (2021) https://doi.org/10.1117/12.2617296
Event: Tenth International Symposium on Precision Mechanical Measurements, 2021, Qingdao, China

Abstract

Stability detection of melt pool has become a challenging task in laser cladding, due to the high temperature and brightness during laser cladding. In this paper, an enhanced mask R-CNN for object instance segmentation of melt pool is proposed to boost the performance of detection. In order to enrich the dataset and improve the generalization of the neural network, the data enhancement method of elastic deformations is used to simulate the irregular deformation of melt pool topography caused by the interference of the external environment. Meanwhile, the MobilenetV2 structure is introduced into mask R-CNN to solve the problem of a large number of parameters and slow running speed of network model, and transformer model was used to replace the classifier of the original network. Experimental results show that the proposed method can improve testing speed by 14.7% without decreasing the segmentation accuracy. Finally, a dynamic stability detection method of melt pool is proposed in this paper.

Citation Download Citation

Linhang Li, Zhenying Xu, Yucheng Tao, Qinghua Liu, and Yuxuan Zhang "Stability detection of melt pool in laser cladding based on enhanced mask R-CNN", Proc. SPIE 12059, Tenth International Symposium on Precision Mechanical Measurements, 120591Z (19 November 2021); https://doi.org/10.1117/12.2617296

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