摘要
针对高熔点合金焊接中由于焊接力过大导致搅拌头断裂的问题,建立搅拌头的焊接力预测模型。根据搅拌摩擦焊接过程中搅拌头与工件间的挤压与摩擦状态,分析考虑温变效应的搅拌头面力分布。考虑接头的温度分布,构建基于微元积分的搅拌头受力模型。将温变热物性参数嵌入到Deform-3D仿真软件中模拟钛合金焊接过程中的温度场,并据此分析搅拌头所受的正压力。根据受力模型预测搅拌头上各部位的受力,并与试验结果进行对比,验证预测模型的可靠性。预测结果显示,搅拌头所受前进阻力主要由搅拌针承受,各部位所受扭矩百分比与各部位面积百分比相近,而各部位所受顶锻力百分比与各部位面积百分比无关。
The welding force prediction model of stirring head was established in view of the fracture of stirring head caused by excessive welding force in the welding of high melting point alloy.The surface force distribution of the stirring head considering temperature change effect was analyzed according to the extrusion and friction between the stirring head and the workpiece in the process of friction stir welding.Considering the temperature distribution of the weld joint,the force model of the stirring head based on the micro integral was established.The temperature field in titanium alloy welding process was simulated by embedding the physical parameters of temperature heating into Deform-3D,and the positive pressure on the stirring head was analyzed.According to the force model,the force on each part of the stirring head was predicted and compared with the experimental results to verify the reliability of the prediction model.The prediction results show that the forward resistance of the stirring head is mainly borne by the pin,and the percentage of the torque at each part is close to the percentage of area at each part,while the percentage of the forging force at each part has nothing to do with the percentage of area at each part.
作者
翁飞翔
王庆霞
吴重军
孙立凡
WENG Feixiang;WANG Qingxia;WU Chongjun;SUN Lifan(College of Mechanical EngineeringDonghua University,Shanghai 201620,China;Shanghai Aerospace Process and Equipment Engineering Technology Research Center,Donghua University,Shanghai 201620,China;Shanghai Aerospace Equipment Manufacture Co.Ltd.,Shanghai 200240,China)
出处
《东华大学学报（自然科学版）》
CAS
北大核心
2022年第6期103-111,共9页
Journal of Donghua University(Natural Science)
关键词
搅拌摩擦焊
搅拌头
焊接力
温度分布
预测模型
friction stir welding
stirring head
welding force
temperature distribution
prediction model
