【作者】 胡静；

【导师】 谢延敏；

【作者基本信息】 西南交通大学 ， 机械制造及其自动化， 2013， 硕士

【摘要】 板料成形作为现代工业的一种非常重要的加工方法,用以生产各种板材零件,在航空航天、国防、汽车等领域得到了广泛的应用。随着数值模拟技术的不断发展,对板料成形进行有限元分析,可以缩短模具的生产周期和降低生产成本。然而,对于较为复杂的成形件,数值模拟需要耗费大量的时间,同时成形件在生产过程中受到工艺条件、材料性能等波动的影响,成形件的质量可能达不到要求。因此,需要对板料的成形过程进行稳健设计,使得板料成形质量对于工艺条件、材料性能等参数的波动不敏感。将Kriging代理模型应用于板料成形优化中,可以减少板料成形数值模拟的时间,提高优化效率。结合灰色关联分析对Kring模型的随机分布部分中的θ值进行优化,在不增加样本点的情况下提高了Kriging模型的精度。将改进后的Kriging模型应用于NUMISHEET93会议中方盒件的成形缺陷的预测,与未优化的Kriging模型相比,模型的精度大大提高。为了使得板料的成形质量对于工艺条件、材料性能等参数波动的不敏感,提出了基于Dual-Kriging的多目标稳健设计方法。筛选影响油底壳成形质量的可控以及噪声因子并且确定其相应的波动范围；基于有限元分析应用改进的Kriging模型建立可控与噪声因子与成形件质量的映射关系；根据参数波动,基于第一重Kriging模型、蒙特卡罗模拟得到成形质量的期望与方差,建立成形质量期望与方差的第二重Kriging模型；应用基于拥挤距离的多目标粒子群算法对稳健模型进行优化。结果表明,与传统确定性优化相比,成形件质量的波动范围明显减小,提高了成形件的稳健性。更多还原

【Abstract】 As one of the important processing method in the modem industry, sheet metal forming is used to produce a variety of sheet metal parts and has been widely applied in aerospace, defense, automotive and other fields. With the continuous development of the numerical simulation technology, the cycle of the mold production and product cost can be shortened by using the finite element to analyze the sheet metal forming. However, for the more complex forming parts, numerical simulation takes too much time. At the same time, the quality of the forming parts will be below the standard, affected by the fluctuations of the process conditions and the material properties in the production process. Therefore, the robust design should be applied for the metal forming process. It will make the forming quality of the sheet be not sensitive to the process conditions, material properties and so on.Kriging surrogate model is applied to optimize the sheet metal forming and it can reduce the time of the numerical simulation and enhance the optimization efficiency. The theta value of the random distribution of the Kriging model is optimized with the grey relational analysis and it can improve the accuracy of Kriging model without increasing the other sample points. Improved Kriging model is applied to predict the forming defects of the square box in Numisheet93. Compared to the unoptimized Kriging model, the accuracy of the model is greatly improved.To make the forming quality of the sheet metal be not sensitive to the fluctuation of the process condition, the material properties and so on, the robust design based on the Dual-Kriging model is put forward. The controllable factors and noise factors which affect the forming quality are chosen and their corresponding fluctuation range is determined. The function of the controllable factors and noise factors and quality of the forming parts is established using the improved Kriging model based on the numerical simulation. The second layer Kriging model of the forming quality and variance is built based on the first layer Kriging model and Monte Carlo simulation according to the parameters fluctuation. The robust model is optimized with the multi-objective particle swarm optimization algorithm based on the crowding distance. The result shows that, compared to the traditional deterministic optimization, the fluctuation range of the quality of the forming part is effectively reduced and the robustness is improved.更多还原