Prediction of Single Weld Bead Size of TIG Welding Arc Additive Manufacturing
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摘要: 利用钨极惰性气体（TIG）保护焊电弧增材制造平台对GH4169镍基高温合金进行正交试验，研究了焊接电流、焊接速度、送丝速度对焊道熔宽和余高的影响；建立了BP人工神经网络，利用遗传算法对其进行优化，得到了单焊道尺寸预测模型，并基于MATLAB的图形用户界面模块（GUI）创建了预测人工交互界面。结果表明：焊道熔宽随焊接电流增加而增大，随焊接速度增加而降低，随送丝速度增加则先增大后降低；焊道余高与送丝速度呈线性正相关，与焊接电流和焊接速度则呈负相关；该焊道尺寸预测模型的相对误差在6%以内，能够较为准确地预测单焊道的形状与尺寸。Abstract: Orthogonal test of GH4169 nickel-based superalloy was carried out with the tungsten inert gas (TIG) welding arc additive manufacturing platform. Effects of welding current, welding speed, and wire feeding speed on weld width and reinforcement were studied. BP artificial neural network was established and optimized by genetic algorithm, the single weld bead shape and size prediction model was obtained, and a human interactive interface for size prediction was created by the graphical user interface (GUI) module of MATLAB. The results show that the weld width increased with the welding current, decreased with increasing welding speed, and first increased and then decreased with increasing wire feeding speed. The weld bead reinforcement was linearly positively correlated with the wire feeding speed, and negatively correlated with welding current and welding speed. The prediction relative error of the weld bead size prediction model was within 6%, which could predict the shape and size of a single weld bead more accurately.
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Keywords:
- arc additive manufacturing /
- weld bead size /
- BP neural network /
- prediction model
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