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以汽车显示仪框的注塑成型为例,构建了该汽车塑件两种浇注方案的CAE分析模型,得到了最佳浇注方案,运用Moldflow软件对塑件的注塑成型工艺参数进行了仿真,并对塑件注塑过程中的翘曲、熔接痕、气穴等缺陷成因进行了分析,给出了质量改善优化目标,最后提出了一种新的结合Tugachi试验法、BP神经网络预测的注塑成型工艺寻优方法,并对寻优结果进行了CAE模流分析验证。结果表明:神经网络预测结果与CAE模流分析结果相近,运用Tugachi正交试验分析、BP神经网络、CAE模流分析相结合的方法,能获得较佳的注塑成型工艺参数,使汽车塑件的注塑质量得到明显改善。
Take the automobile display frame injection molding as an example, the CAE analysis model of two kinds of injection molding schemes of the automobile plastic parts is constructed, the best casting scheme is obtained, the injection molding process parameters of the plastic parts are simulated by using the Moldflow software, The causes of defects such as warpage, welding marks and cavitation in the plastic injection molding process are analyzed, and the goal of quality improvement is given. Finally, a new Tugachi test method and BP neural network prediction injection molding process are proposed Excellent method, and the result of the optimization was verified by CAE mode flow analysis. The results show that the prediction results of neural network are similar to those of CAE mode flow analysis. By using Tugachi orthogonal test analysis, BP neural network and CAE mode flow analysis, the better injection molding process parameters can be obtained, Injection molding quality has been significantly improved.