车用CD托架CAE注塑工艺参数优化分析 |
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引用本文: | 张建卿. 车用CD托架CAE注塑工艺参数优化分析[J]. 工程塑料应用, 2016, 0(7): 73-78. DOI: 10.3969/j.issn.1001-3539.2016.07.014 |
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作者姓名: | 张建卿 |
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作者单位: | 怀化职业技术学院,湖南怀化,418000 |
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基金项目: | 湖南省教育厅资助项目(13C1170) |
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摘 要: | 以汽车CD托架注塑成型为例,结合生产实际问题,构建了产品CAE分析模型,运用Moldfl ow2015软件对产品材料推荐的注塑成型工艺参数进行了初步仿真,对注塑过程中的翘曲、熔接痕、气穴等缺陷成因进行了分析,并给出了质量改善优化目标,提出了一种结合Taguchi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,产品翘曲量降低至1.192 mm,产品较佳的注塑成型工艺参数为:料温为225℃,模温为60℃,注塑压力为70 MPa,注塑时间为1.3 s,第一保压压力为80 MPa,第一保压时间为12 s,第二保压压力为30 MPa,第二保压时间为3 s,冷却时间为15 s,型腔随形水路C1,C2冷却水的温度均为30℃。提出的优化设计方法能有效降低模具试模成本,缩短模具生产周期。
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关 键 词: | CD托架 CAE分析 BP神经网络 正交试验 注塑成型 |
CAE Optimization Analysis of Injection Process Parameters for Automobile CD Bracket |
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Abstract: | Taked the CD bracket of automobile as an example,the product CAE analysis model was built with the practical problems in production,and the Moldflow 2015 software was used to recommend the product. Plastic molding process parameters had carried on the preliminary simulation,injection molding warpage,weld marks,cavitation and other causes of defects were ana-lyzed,and the quality improvement and optimization of the target were given,an injection molding process optimization method based on Taguchi test methodand BP neural network is proposed,and the optimization results were verified by CAE mode flow analysis. The results show that neural network prediction results is similar to that of CAE mode flow analysis,the warpage amount is reduced to 1.192 mm,the injection molding process parameters with better products are as follows:raw material temperature is 225℃,mold temperature is 60℃, injection pressure is 70 MPa,injection time is 1.3 s,first holding pressure is 80 MPa,first pres-sure holding time is 12 s,second holding pressure is 30 MPa,second pressure holding time is 3 s,cooling time is 15 s,the water temperature of C1,C2 waterways for cooling cavity is 30℃. The proposed optimization design method can effectively reduce the molding test cost,short the mold production cycle. |
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Keywords: | CD bracket CAE analysis BP neural network orthogonal test injection molding |
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