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焊接热输入对高速动车组转向架侧梁焊接变形的影响及优化

Effect of welding heat input on welding deformation of bogie side beam of high-speed EMU and optimization

  • 摘要: 转向架构架是高速动车组(electric multiple units, EMU)的重要承载部件,其侧梁的焊接质量直接关系到列车运行的平顺性及安全性. 为了研究焊接热输入对转向架侧梁焊接变形的影响,在侧梁结构中提取了曲线T形接头模型,以熔化极气体保护电弧焊(gas metal arc welding, GMAW)的焊接速度、焊接电流和焊接电压为研究对象,基于热机耦合仿真分析方法和具有交互作用的正交试验设计(design of experimental, DOE)方法建立代理模型,采用粒子群优化算法(particle swarm optimization, PSO)获得了最优的焊接工艺参数组合. 在此基础上,基于极差分析和方差分析(analysis of variance, ANOVA),进一步讨论了上述工艺参数对焊接热输入和焊接残余变形的影响. 结果表明,采用最优工艺参数的曲线T形接头模型焊接角变形比采用原生产工艺参数的结果降低了5.04%,采用最优工艺参数的侧梁模型可以保证上下盖板焊接残余变形满足平面度不大于1 mm的要求,无需焊后调平.

     

    Abstract: Bogie is an important part of high-speed electric multiple units (EMU), the welding quality of bogie side beam is directly related to the smoothness and safety of the railway vehicle. In order to study the effect of welding heat input on the welding residual deformation of bogie side beam, the curve T-joint model was extracted from the bogie side beam. Taking welding speed, welding current and welding voltage of gas metal arc welding (GMAW) as research objects, the surrogate model was established based on the thermal-mechanical coupling simulation analysis method and orthogonal design of experimental (DOE) method with interaction, and the optimal combination of process parameters is obtained based on particle swarm optimization (PSO) algorithm. The influence of above parameters on welding heat input and welding residual deformation is further discussed using range analysis and analysis of variance (ANOVA). Applying the optimal welding process parameters and production process parameters to curve T-joint model and the bogie side beam, respectively, the angular deformation result of the curve T-joint model using the optimal process parameters is 5.04% better than the result using the production parameters, and the welding residual deformation of the upper and lower cover plates of the side beam can be guaranteed to meet the requirement of flatness 1 mm without post-welding treatment.

     

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