Prediction of powder bed thickness by spatter detection from coaxial optical images in selective laser melting of 316L stainless steel
文献类型：期刊论文
| 作者 | Zhang, Weihao1,2; Ma, Honglin1,3 ; Zhang, Qi1,3; Fan, Shuqian1,3
|
| 刊名 | MATERIALS & DESIGN
 |
| 出版日期 | 2022 |
| 卷号 | 213页码:12 |
| 关键词 | Additive manufacturing Selective laser melting Spatter Coaxial monitoring High-speed imaging Machine vision |
| ISSN号 | 0264-1275 |
| DOI | 10.1016/j.matdes.2021.110301 |
| 通讯作者 | Zhang, Qi(zhangqi@cigit.ac.cn) ; Fan, Shuqian(fansq@cigit.ac.cn) |
| 英文摘要 | The uniformity of a recoated powder layer affects the performance of parts manufactured by SLM directly, while it is related to the characteristics of spatters. The small spatter moves pretty fast, while the low optical transmittance in the spectrum of a hot spatter in the coaxial optical path of SLM equipment prevents clear imaging of this target with high contrast. In this study, a coaxial optical path with an enhanced optical transmittance is used for imaging the melt pool and its surrounding phenomena simultaneously. An experimental system was developed using a high-speed camera for coaxial observation of hot spatters in the SLM process. The problems of limited field of view and high measurement uncertainty of an off-axis process monitoring system are solved. For defocused and distorted spatter images, both a segmentation algorithm and an object detection method have been proposed and proved to be effective. It was found that the direction and strength of the local airflow field could be estimated via the curvature of the spatter trajectory. More importantly, the quantity of spatters detected is positively related to the amount of powder locally distributed on the baseplate, which is useful to estimate the powder bed thickness at this position. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| 资助项目 | National Key Research and Development Program of China[2016YFC1100500] ; National Natural Science Foundation of China[51675507] ; Youth Innovation Promotion Association, CAS |
| WOS研究方向 | Materials Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000734388700003 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/14939]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Zhang, Qi; Fan, Shuqian |
| 作者单位 | 1.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China 2.Univ Chinese Acad Sci, Chongqing Sch, Chongqing 400714, Peoples R China 3.Chongqing Key Lab Addit Mfg Technol & Syst, Chongqing 400714, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Weihao,Ma, Honglin,Zhang, Qi,et al. Prediction of powder bed thickness by spatter detection from coaxial optical images in selective laser melting of 316L stainless steel[J]. MATERIALS & DESIGN,2022,213:12. |
| APA | Zhang, Weihao,Ma, Honglin,Zhang, Qi,&Fan, Shuqian.(2022).Prediction of powder bed thickness by spatter detection from coaxial optical images in selective laser melting of 316L stainless steel.MATERIALS & DESIGN,213,12. |
| MLA | Zhang, Weihao,et al."Prediction of powder bed thickness by spatter detection from coaxial optical images in selective laser melting of 316L stainless steel".MATERIALS & DESIGN 213(2022):12. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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