Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks

@article{Zhang2020PowderBedFP,
  title={Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks},
  author={Yingjie Zhang and Hong Geok Soon and Dongsen Ye and Jerry Ying Hsi Fuh and Kunpeng Zhu},
  journal={IEEE Transactions on Industrial Informatics},
  year={2020},
  volume={16},
  pages={5769-5779}
}
In this article, a method of hybrid convolutional neural networks (CNNs) is proposed for powder-bed fusion (PBF) process monitoring. The proposed method can learn both the spatial and temporal representative features from the raw images automatically based on the advantages of the CNN architecture. The results demonstrate the superior performance of the proposed method compared with the traditional methods with handcrafted features. The overall detection accuracy of four process conditions, e.g… 
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