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code for KBS paper "Cross-attention-based multi-sensing signals fusion for penetration state monitoring during laser welding of aluminum alloy"

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hxf1228/cafnet-laser-welding

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CAFNet for Laser Welding Monitoring

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This repository contains source code for KBS paper "Cross-attention-based multi-sensing signals fusion for penetration state monitoring during laser welding of aluminum alloy".

Codes are run on Ubuntu 22.04 with an Nvidia RTX 2080 GPU.

Note: Due to the requirements of project, raw datasets used in the paper are not provided.

Citation

If this project useful for your research, please cite the original journal paper with the following BibTex entry.

@article{cao_cross-attention-based_2023,
	title = {Cross-attention-based multi-sensing signals fusion for penetration state monitoring during laser welding of aluminum alloy},
	volume = {261},
	issn = {0950-7051},
	url = {https://www.sciencedirect.com/science/article/pii/S0950705122013089},
	doi = {https://doi.org/10.1016/j.knosys.2022.110212},
	journal = {Knowledge-Based Systems},
	author = {Cao, Longchao and Li, Jingchang and Zhang, Libin and Luo, Shuyang and Li, Menglei and Huang, Xufeng},
	year = {2023},
	pages = {110212},
}

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code for KBS paper "Cross-attention-based multi-sensing signals fusion for penetration state monitoring during laser welding of aluminum alloy"

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