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作 者:赵亮[1] 彭琳[2] ZHAO Liang;PENG Lin(Shanxi Institute of Mechanical and Electrical Engineering,Shanxi Changzhi 046011,China;College of Basic and Information Engineering,Yunnan Agricultural University,Yunnan Kunming 650500,China)
机构地区:[1]山西机电职业技术学院,山西长治046011 [2]云南农业大学基础与信息工程学院,云南昆明650500
出 处:《机械设计与制造》2025年第2期280-284,288,共6页Machinery Design & Manufacture
基 金:山西省教育科学“十三五”规划2018年度专项课题(GH-18151)。
摘 要:为了减小汽车中立柱冲压成形的最大减薄率和最大增厚率,提出了基于新型选择NSGA-Ⅱ算法的冲压优化方法。介绍了中立柱冲压成形工艺和高强度钢材料;以最小化最大减薄率和最大增厚率为目标,建立了多目标优化模型;使用最优拉丁超立方抽样法在优化空间抽取了30个采样点,借助AutoForm R7软件得到相应的最大减薄率和最大增厚率;使用3阶响应面模型拟合了参数间回归模型,并验证了模型的回归精度。给出了融合非支配排序层和自身累积被支配数的新型选择策略,并将其融入到NSGA-Ⅱ算法中,提出了新型选择NSGA-II算法,并将该算法应用于优化模型求解。经生产验证,最大减薄率均值由当13.1%减小为11.6%,最大增厚率均值由1.05%减小为0.98%,验证了这里的方法在中立柱冲压优化中的有效性。In order to reduce the maximum thinning rate and maximum thickening rate of automotive column stamping,a stamp⁃ing optimization method based on cumulative non-dominated assignment NSGA-II algorithm is proposed.The stamping forming process and high strength steel material of middle column are introduced;A multi-objective optimization model is established to minimize the maximum thinning rate and maximum thickening rate;The optimal Latin hypercube sampling method is used to ex⁃tract 30 sampling points in the optimized space,and the corresponding maximum thinning rate and maximum thickening rate are obtained with the help of AutoForm R7 software;The third-order response surface model is used to fit the regression model between parameters,and the regression accuracy of the model is verified.The cumulative non dominated assignment method is integrated into NSGA-II algorithm,and the cumulative non dominated assignment NSGA-II algorithm is proposed and applied to the opti⁃mization model.The production verification shows that the average value of the maximum thinning rate is reduced from 13.1%to 11.6%,and the average value of the maximum thickening rate is reduced from 1.05%to 0.98%,which verifies the effectiveness of this method in the stamping optimization of middle column.
关 键 词:汽车中立柱 高强度钢 新型选择策略 多目标优化 响应面模型
分 类 号:TH16[机械工程—机械制造及自动化] TG386[金属学及工艺—金属压力加工]
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