USING COAXIAL MELT POOL MONITORING IMAGES TO ESTIMATE COOLING RATE FOR POWDER BED FUSION ADDITIVE MANUFACTURING

被引:0
作者
Yang, Zhuo [1 ,2 ]
Lane, Brandon [2 ]
Lu, Yan [2 ]
Yeung, Ho [2 ]
Kim, Jaehyuk [2 ]
Ndiaye, Yande [2 ]
Krishnamurty, Sundar [3 ]
机构
[1] Georgetown Univ, Washington, DC 20057 USA
[2] NIST, Gaithersburg, MD 20899 USA
[3] Univ Massachusetts, Amherst, MA 01003 USA
来源
PROCEEDINGS OF ASME 2022 INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, IDETC-CIE2022, VOL 2 | 2022年
关键词
Cooling rate; additive manufacturing; powder bed fusion; in-situ monitoring; coaxial melt pool monitoring; LASER;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cooling rate is a decisive index to characterize melt pool solidification and determine local microstructure formation in metal powder bed fusion processes. Traditional methods to estimate the cooling rate include in-situ temperature measurement and thermal simulation. However, these methods may not be accurate or efficient enough under complex conditions in real-time. This paper proposes a method to approximate the melt pool cooling rate using temperature profile acquired via thermally-calibrated melt pool camera, and based on continuous pixel tracking result. The proposed method can estimate the temperature and associated cooling rate for every pixel immediately, which is potentially applicable for real-time process monitoring. This paper focuses on investigating image data processing, method development, and cooling condition analysis. This work presents the preliminary result of the cooling rate estimation under different conditions such as position, layer number, and overhanging.
引用
收藏
页数:9
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