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《工程塑料应用》 2021年第02期
DOI:10.3969/j.issn.1001-3539.2021.02.013
基于Taguchi与BPNN-PSO的薄壁注塑件翘曲变形优化
刘锋123,庞建军14,陈宇轩1,丁明明14
1.浙江水利水电学院机械与汽车工程学院,杭州 310018; 2.浙江工业大学机械工程学院,杭州 310023; 3.华中科技大学材料成形与模具技术国家重点实验室,武汉 430074; 4.先进水利装备浙江省工程研究中心,杭州 310018 
Optimization of Warpage Deformation of Thin-wall Injection Molded Part based on Taguchi Test and BPNN-PSO
Liu Feng123, Pang Jianjun14, Chen Yuxuan1, Ding Mingming14
1. School of Mechanical and Automotive Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China; 2. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; 3. State Key Lab of Materials Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, China; 4. Zhejiang Engineering Research Center for Advanced Hydraulic Equipment, Hangzhou 310018, China 
摘要:以家用空调遥控器前壳注塑件为例,在应用CAE模流分析确定塑件浇注系统和冷却系统的基础上,选取模具温度、熔体温度、注塑时间、保压时间和保压压力为设计变量,通过集成有限元模拟、Taguchi正交试验、BP神经网络(BPNN)以及粒子群优化算法(PSO)等来实现对薄壁塑件翘曲变形量的优化。优化后的工艺参数使得塑件翘曲变形量较优化前减少了37%,并应用Moldflow对优化工艺参数可靠性进行了模拟验证,结果显示,验证值和优化结果吻合度高,仅相差0.015 mm,表明所采用的薄壁塑件翘曲变形优化方法能显著减少注塑工艺参数调控过程对操作人员的经验依赖,具有较高的工程应用价值。 
Abstract:The remote control front shell of the household appliance air conditioner was took as an injection molded part example, the injection system and cooling system of the plastic part was determined based on the application of CAE mold flow analysis, the mold temperature, melt temperature, injection time, holding pressure time, and holding pressure were selected as the design variables. The warpage deformation optimization result of the thin wall injection molded part was achieved by integrated finite element simulation, Taguchi method, BP neural network (BPNN) and particle swarm optimization (PSO) methods. The plastic part warpage deformation is reduced by 37% after optimization, and the optimization result reliability is verified by the Moldflow simulation analysis as well, the analysis result shows that the verification result and the optimized result are in good agreement, with a difference of only 0.015 mm, which indicates that the experience dependence of the injection process parameter adjustment process on the operator can be significantly reduced by the proposed optimization design method, and this optimization method has a high engineering application value. 
关键词:注射成型;Moldflow;Taguchi试验;BP神经网络;粒子群优化算法;翘曲变形优化 
Keywords:injection molding; Moldflow; Taguchi test; BP neural network; particle swarm optimization; warpage deformation optimization 
基金:浙江省自然科学基金项目(LY19E050009),浙江省省级重点研发计划项目(2020C01062),材料成形与模具技术国家重点实验室开放基金项目(P2021-22),浙江省水利厅科技计划项目(RC2022) 
本文引用格式:
刘锋,庞建军,陈宇轩,等.基于Taguchi与BPNN-PSO的薄壁注塑件翘曲变形优化[J].工程塑料应用,2021,49(2):74-79.
Liu Feng,Pang Jianjun,Chen Yuxuan,et al. Optimization of warpage deformation of thin-wall injection molded part based on taguchi test and BPNN-PSO[J]. Engineering Plastics Application,2021,49(2):74-79. 

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