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基于GRA-RSM的排气尾管冲压多工序精度传递预测与控制
英文标题:Prediction and control on stamping multi-process precision transfer for exhaust tail pipe based on GRA-RSM
作者:董翔 宋燕利 沈海波 路珏 李玮灏 
单位:武汉理工大学 现代汽车零部件技术湖北省重点实验室  武汉理工大学 汽车工程学院 赛恩特实业有限公司 
关键词:排气尾管 回弹 灰色关联分析 传递模型 精度预测 
分类号:TP182
出版年,卷(期):页码:2022,47(11):101-108
摘要:

为了提高不锈钢排气尾管的成形质量,提出了基于变形回弹的冲压多工序精度传递预测与控制方法。以选取的点云处的均方根回弹值作为精度评价指标,考虑到拉延和卷圆工序对构件回弹值的复合叠加效果,通过灰色关联分析法筛选出与评价指标关联度较大的影响因素,建立了基于响应面法的精度传递预测模型,对回弹造成的误差在时域上的传递进行了表征。采用遗传算法对上述模型进行求解,得到拉延-卷圆工序的最佳工艺参数,使得排气尾管成形后的回弹最大值降低了13.2%,均方根回弹值降低了12.2%,各测量点的回弹值差异减少,有效地提升了排气尾管的成形精度,有利于提高后续焊接工艺质量的稳定性。

In order to improve the forming quality of stainless steel exhaust tail pipe, a prediction and control method of stamping multi-process precision transfer based on deformation springback was proposed. Taking the root mean square springback value at the selected point cloud as the precision evaluation index, considering the composite superposition effect of drawing and rolling processes on the workpiece springback value, the influencing factors that were closed related to the evaluation index were screened out by the grey relational analysis method, the precision transfer prediction model based on response surface method was established, and the transmission of the error caused by springback in the time domain was characterized. Then, the above model was solved by the genetic algorithm, and the optimal process parameters of drawing and rolling processes were obtained, which reduced the maximum springback value of the exhaust tail pipe after forming by 13.2% and the root mean square springback value by 12.2%. Thus, the difference of springback values at various measuring points was reduced, which effectively improved the forming precision of the exhaust tail pipe and was beneficial to improve the quality stability for the subsequent welding process.

基金项目:
国家自然科学基金资助项目(51975440);新能源汽车科学与关键技术学科创新引智基地项目(B17034);教育部创新团队发展计划(IRT13087);湖北省重点研发计划(2020BAB143)
作者简介:
作者简介:董翔(1997-),男,硕士研究生,E-mail:Xiangdong9709@163.com;通信作者:宋燕利(1979-),男,博士,教授,E-mail:ylsong@whut.edu.cn
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