摘要
针对塑料制品在注塑过程产生的体积收缩和翘曲变形等缺陷,提出一种多元高次回归分析模型建立方法。将体积收缩率和翘曲变形量多目标优化问题通过改进的折衷规划法转换成综合目标函数优化问题。以模具温度、熔体温度、注射时间、保压时间和保压压力作为优化参数,设计并完成了均匀设计试验,根据试验数据构建了多元高次回归分析模型,用标准粒子群算法对回归模型进行寻优求解。以汽车全塑前端框架为例,运用上述方法得到体积收缩率12.41%,翘曲变形量为0.69 mm,对应的模具温度为74℃、熔体温度290℃、注射时间2.91 s、保压时间45.5 s和保压压力58 MPa。运用该方法得到的最佳工艺参数组合有效降低了体积收缩率和翘曲变形量,为实际生产提供了帮助。
Aiming at the defects,such as,volume shrinkage and warping deformation caused by plastic products in the process of injection molding,a method of establishing multiple high-order regression analysis model was proposed.The multi-objective optimization problem of volume shrinkage and warping deformation was transformed into the comprehensive objective function optimization problem by the improved compromise programming method.Taking mold temperature,melt temperature,injection time,pressure holding time and pressure holding pressure as optimization parameters,uniform design test was designed and completed.A multiple high-order regression analysis model was built according to the test data,and the regression model was optimized by particle swarm optimization algorithm.Taking the full-plastic front frame of automobile as an example,the volume shrinkage rate is 12.41%,the warped deformation is 0.69 mm,and the corresponding mold temperature is 74℃,melt temperature is 290℃,injection time is 2.91 s,pressure holding time is 45.5 s and pressure holding pressure is 58 MPa.The optimum combination of process parameters obtained by this method can effectively reduce the volume shrinkage rate and the amount of warping deformation,which is helpful for the actual production.
作者
吴鹏
王幼民
刘司诚
杨德玉
WU Peng;WANG You-min;LIU Si-cheng;YANG De-yu(School of Mechanical and Automotive Engineering,Anhui Polytechnic University,Wuhu 241000,China;Anhui Dachang Technology Incorporated Company,Wuhu 241000,China)
出处
《塑料工业》
CAS
CSCD
北大核心
2020年第9期71-75,共5页
China Plastics Industry
关键词
注塑成型
折衷规划法
均匀设计试验
回归分析
粒子群算法
参数优化
Injection Molding
Compromise Planning Method
Uniform Design Experiment
Regression Analysis
Particle Swarm Optimization
Parameters Optimization
