Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks
文献类型：期刊论文
| 作者 | Zhang, Yingjie1,2; Soon, Hong Geok1,2; Ye, Dongsen3; Fuh, Jerry Ying Hsi1,2; Zhu, Kunpeng3 |
| 刊名 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
 |
| 出版日期 | 2020-09-01 |
| 卷号 | 16 |
| 关键词 | Feature extraction Cameras Fiber lasers Laser modes Convolutional neural nets Additive manufacturing condition monitoring convolutional neural networks (CNNs) melt-pool-affected zone powder-bed fusion (PBF) |
| ISSN号 | 1551-3203 |
| DOI | 10.1109/TII.2019.2956078 |
| 通讯作者 | Zhu, Kunpeng(zhukp@iamt.ac.cn) |
| 英文摘要 | 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., overheating, normal, irregularity, and balling, can be up to 0.997. In addition, it is found that the temporal information for PBF process monitoring by the vision detection of the process zone (including melt pool, plume, and spatters) is significant. As the proposed method can save image processing steps, it simplifies the procedure on feature extraction. This makes it more suitable for online monitoring applications. |
| WOS关键词 | RECOGNITION |
| 资助项目 | National Natural Science Foundation of China[51875379] ; National Additive Manufacturing Innovation Cluster, Singapore, under a PEP Project ; IDI Laser Services Pte Ltd., Singapore |
| WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000542966300013 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; National Additive Manufacturing Innovation Cluster, Singapore, under a PEP Project ; IDI Laser Services Pte Ltd., Singapore |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/71067]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Zhu, Kunpeng |
| 作者单位 | 1.Natl Univ Singapore, Dept Mech Engn, Singapore 119077, Singapore 2.NUS Res Inst NUSRI, Suzhou Ind Pk, Suzhou 215123, Peoples R China 3.Chinese Acad Sci, Inst Adv Mfg Technol, Changzhou 213164, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Yingjie,Soon, Hong Geok,Ye, Dongsen,et al. Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2020,16. |
| APA | Zhang, Yingjie,Soon, Hong Geok,Ye, Dongsen,Fuh, Jerry Ying Hsi,&Zhu, Kunpeng.(2020).Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,16. |
| MLA | Zhang, Yingjie,et al."Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 16(2020). |
入库方式： OAI收割
来源：合肥物质科学研究院
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