Prediction of multi-bead profile of robotic wire and arc additive manufactured components recursively using axisymmetric drop shape analysis

被引:7
作者
Chen, Changrong [1 ,2 ]
He, Hua [2 ]
Zhou, Sunsheng [2 ]
Lian, Guofu [1 ,2 ]
Huang, Xu [1 ,2 ]
Feng, Meiyan [1 ,2 ]
机构
[1] Fujian Univ Technol, Fujian Key Lab Intelligent Machining Technol & Equ, Fuzhou 350118, Peoples R China
[2] Fujian Univ Technol, Sch Mech & Automot Engn, Fuzhou 350118, Peoples R China
关键词
Wire and arc additive manufacturing (WAAM); recursive bead profile; multi-bead overlapping model; axisymmetric drop shape analysis (ADSA); surface topography; INTERFACIAL-TENSIONS; OVERLAPPING MODEL; LASER; PENDANT; OPTIMIZATION; PARAMETERS; DEPOSITION; EFFICIENCY; GEOMETRY; SESSILE;
D O I
10.1080/17452759.2023.2254563
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Dimension prediction of robotic wire and arc additive manufacturing (WAAM) part is fundamentally dependent on the modelling accuracy of single-bead profile and its subsequent overlapping ones. Current multi-bead overlapping models are still not capable of describing the flatten valley area of WAAM parts. This paper proposes a new recursive model, based on coordinate transformation and axisymmetric drop shape analysis (ADSA), to predict multi-bead overlapping profiles. First, a single-bead profile model for WAAM is established based on ADSA, followed by detailed description of conventional and proposed modified recursive ADSA profile model. The properties of developed recursive ADSA model are then investigated to reveal the effects of overlapping ratio and single-bead aspect ratio. Finally, multi-bead overlapping deposition experiment is carried out to validate the model feasibility. The results show that the modified recursive ADSA model is more accurate than the conventional one for its better accountability of valley areas. It is also indicated that the modified recursive ADSA model is suitable for the robotic WAAM process. The research outcome is beneficial to improving the forming accuracy of WAAM parts and geometry prediction of other additive manufactured products.
引用
收藏
页数:24
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