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
相关论文
共 50 条
  • [1] CAMERA-BASED COAXIAL MELT POOL MONITORING DATA REGISTRATION FOR LASER POWDER BED FUSION ADDITIVE MANUFACTURING
    Lu, Yan
    Yang, Zhuo
    Kim, Jaehyuk
    Cho, Hyunbo
    Yeung, Ho
    PROCEEDINGS OF THE ASME 2020 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, IMECE2020, VOL 2B, 2020,
  • [2] Deep learning-based data registration of melt-pool-monitoring images for laser powder bed fusion additive manufacturing
    Kim, Jaehyuk
    Yang, Zhuo
    Ko, Hyunwoong
    Cho, Hyunbo
    Lu, Yan
    JOURNAL OF MANUFACTURING SYSTEMS, 2023, 68 : 117 - 129
  • [3] Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing
    Gaikwad, Aniruddha
    Williams, Richard J.
    de Winton, Harry
    Bevans, Benjamin D.
    Smoqi, Ziyad
    Rao, Prahalada
    Hooper, Paul A.
    MATERIALS & DESIGN, 2022, 221
  • [4] Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion
    Kolb, Tobias
    Elahi, Reza
    Seeger, Jan
    Soris, Mathews
    Scheitler, Christian
    Hentschel, Oliver
    Tremel, Jan
    Schmidt, Michael
    RAPID PROTOTYPING JOURNAL, 2020, 26 (01) : 100 - 106
  • [5] Probabilistic Data-Driven Modeling of a Melt Pool in Laser Powder Bed Fusion Additive Manufacturing
    Fang, Qihang
    Xiong, Gang
    Zhao, Meihua
    Tamir, Tariku Sinshaw
    Shen, Zhen
    Yan, Chao-Bo
    Wang, Fei-Yue
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024,
  • [6] New hammerstein modeling and analysis for controlling melt pool width in powder bed fusion additive manufacturing
    Wang, Dan
    Zhao, Xinyu
    Chen, Xu
    ASME Letters in Dynamic Systems and Control, 2021, 1 (03):
  • [7] Formation processes for large ejecta and interactions with melt pool formation in powder bed fusion additive manufacturing
    Nasser, Abdalla R.
    Gundermann, Molly A.
    Reutzel, Edward W.
    Guerrier, Paul
    Krane, Michael H.
    Weldon, Matthew J.
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [8] Formation processes for large ejecta and interactions with melt pool formation in powder bed fusion additive manufacturing
    Abdalla R. Nassar
    Molly A. Gundermann
    Edward W. Reutzel
    Paul Guerrier
    Michael H. Krane
    Matthew J. Weldon
    Scientific Reports, 9
  • [9] Melt pool temperature and cooling rates in laser powder bed fusion
    Hooper, Paul A.
    ADDITIVE MANUFACTURING, 2018, 22 : 548 - 559
  • [10] Hybrid Modeling Approach for Melt-Pool Prediction in Laser Powder Bed Fusion Additive Manufacturing
    Moges, Tesfaye
    Yang, Zhuo
    Jones, Kevontrez
    Feng, Shaw
    Witherell, Paul
    Lu, Yan
    JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING, 2021, 21 (05)