Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing
Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing
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DOI：
10.1016/j.rcim.2015.12.004
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发表时间：
2016-06-01
影响因子：
10.4
通讯作者：
Larkin, Nathan
中科院分区：
文献类型：
--
作者：
Ding, Donghong;Pan, Zengxi;Larkin, Nathan
线弧增材制造（WAAM）是传统减材制造方法的一种有前途的替代方法，用于制造具有高购买-飞行比率的大型航空航天金属部件。本研究的重点是开发一个自动化制造系统，以摆脱操作员干预的CAD模型的分析，规划的沉积路径，然后手动设置焊接工艺参数。首先，通过人工神经网络（ANN）模型建立了单焊道几何形状与焊接工艺参数之间的关系。然后，介绍了高几何精度无空洞沉积的自适应中轴变换（MAT）算法。自适应MAT路径是通过使用单珠ANN模型与先前开发的多珠重叠模型一起实现的。最后，通过两个金属零件的实验沉积，对自适应MAT路径规划策略和所建立的焊道模型进行了验证。结果表明，开发的珠模型和自适应MAT为基础的路径是能够生产沉积高质量（无空隙）和几何精度，通过自动选择的WAAM过程的过程变量。(C)2015爱思唯尔有限公司版权所有。
Wire and arc additive manufacturing (WAAM) is a promising alternative to traditional subtractive methods for fabricating large aerospace metal components that feature high buy-to-fly ratios. This study focuses on the development of an automated manufacturing system in order to free the operator from intervening in the analysis of the CAD model, planning the deposition path, and then manually setting the welding process parameters. Firstly, the relationship between single bead geometry and welding process parameters is established through an artificial neural network (ANN) model. Then, the adaptive medial axis transformation (MAT) algorithm for void-free deposition with high geometrical accuracy is introduced. The adaptive MAT path is implemented by using the single bead ANN model together with a previously developed multi-bead overlapping model. Finally, the adaptive MAT path planning strategy and the established bead models are tested through experimental deposition of two metal components. The results show that the developed bead model and adaptive MAT-based path are capable of producing depositions with high quality (void-free) and geometrical accuracy through automated selection of process variables for the WAAM process. (C) 2015 Elsevier Ltd. All rights reserved.