基于DOE、正交及PSO的肉品传送齿轮的工艺优化
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摘要
以肉制品链板传送系统中的塑料齿轮为研究对象,利用模流分析软件AMI2015中的试验设计(DOE)模块分析了影响塑料齿轮成型质量的主要注塑工艺参数,以这些主要工艺参数为试验因素进行正交试验设计,并得到了不同工艺参数组合下的模流结果。然后对正交试验数据进行二次回归分析,得出综合质量指标与工艺参数之间的二次回归方程,再通过粒子群优化(PSO)算法优化出最优工艺参数,并采用最优工艺参数分析验证,得出塑料齿轮的最大收缩率为9.019%,最大缩痕指数为2.766%,最大翘曲变形为1.704 mm,综合质量指标Q值为6.199,误差为2.84%。与正交优化相比,PSO优化出的综合质量指标Q值由12.457降为6.199,降低了50.237%。
Based on the plastic gear of meat chain conveyor belt system,the main injection molding parameters affecting the molding quality of plastic gear were analyzed by using the design of experiment(DOE) module in the model flow analysis software AMI2015,which were used as experimental factors of the orthogonal experimental design,and the model flow results with different combination of process parameters were simulated.Then,quadratic regression analysis of the orthogonal test data was carried out,and the regression equation between the comprehensive quality index and the process parameters were obtained.The optimal process parameters were optimized through particle swarm optimization(PSO) algorithm,and optimal process parameters were used for analysis and verification.The maximum shrinkage rate of the plastic gear was 9.019%,the maximum shrinkage index was 2.766%,and the maximum warping deformation was 1.704 mm.The Q value of the comprehensive quality index was 6.199 and the error was 2.84%.Compared with the orthogonal optimization,the Q value of the integrated quality index optimized by PSO decreased from 12.457 to 6.199,which was reduced by 50.237%.
Based on the plastic gear of meat chain conveyor belt system,the main injection molding parameters affecting the molding quality of plastic gear were analyzed by using the design of experiment(DOE) module in the model flow analysis software AMI2015,which were used as experimental factors of the orthogonal experimental design,and the model flow results with different combination of process parameters were simulated.Then,quadratic regression analysis of the orthogonal test data was carried out,and the regression equation between the comprehensive quality index and the process parameters were obtained.The optimal process parameters were optimized through particle swarm optimization(PSO) algorithm,and optimal process parameters were used for analysis and verification.The maximum shrinkage rate of the plastic gear was 9.019%,the maximum shrinkage index was 2.766%,and the maximum warping deformation was 1.704 mm.The Q value of the comprehensive quality index was 6.199 and the error was 2.84%.Compared with the orthogonal optimization,the Q value of the integrated quality index optimized by PSO decreased from 12.457 to 6.199,which was reduced by 50.237%.
引文
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[2]刘月云,刘碧俊.基于BP神经网络及PSO算法的食品输送齿轮注塑工艺参数优化研究[J].塑料科技,2018,46(1):80.
[3]韩淑华,侯学元,李文卿.改进PSO-BP注塑成型工艺参数优化研究[J].机械设计与制造,2015(10):98.
[4]陈巍,周雄辉,张汝珍,等.基于Kriging代理模型的注塑产品翘曲优化[J].上海交通大学学报,2010,44(4):588.
[5]张昉昀,钟汉如.基于Moldflow和DOE技术的翘曲变形工艺优化[J].塑料,2011,40(4):90-92.
[6]屈华昌,吴梦陵,史安娜,等.塑料成型工艺与模具设计[M].3版.北京:高等教育出版社,2014:33.
[7]孙蒙蒙,丁武学,曹春平,等.基于Taguchi DOE和Moldflow的汽车内饰件注射成型工艺参数优化[J].工程塑料应用,2012,40(10):43-46.
[8]成晨,王传洋.基于CAE与DOE的电钻外壳优化设计[J].科学大众:科学教育,2016(9):183.
[9]CHEN W C,KUMNIAWAN D,FU G L.Optimization of process parameters using DOE,RSM,and GA in plastic injection molding[J].Advanced Materials Research,2012,472/473/474/475:1220-1223.
[10]丁清国,刘泓滨.基于CAE和DOE的注塑成型工艺多目标优化研究[J].塑料工业,2012,40(7):56.
[11]段家现.基于CAE的电池后盖注塑成型工艺优化[J].塑料,2015,44(5):41.
[12]刘彦国,孙先明,聂福荣.塑料成型工艺与模具设计[M].3版.北京:人民邮电出版社,2014:91.
[13]孙远韬,秦仙蓉,孙文斌,等.基于正交回归试验法的煤矿剪式抓斗优化设计[J].同济大学学报:自然科学版,2017,45(12):1856.
[14]王小川,史峰,郁磊,等.MATLAB神经网络43个案例分析[M].北京:北京航空航天大学出版社,2013:306.
[15]王道明,鲁昌华,蒋薇薇,等.基于粒子群算法的决策树SVM多分类方法研究[J].电子测量与仪器学报,2015,29(4):611-615.
[16]余建平,周新民,陈明.群体智能典型算法研究综述[J].计算机工程与应用,2010,46(25):4.
[17]KENNEDY J,EBERHART R C.Swarm intelligence[M].San Francisco:Morgan Kaufmann Publisher,2001:165-178.
[18]申元霞,王国胤.新型粒子群优化模型及应用[M].北京:科学出版社,2016:5.
[19]温正.精通MATLAB智能算法[M].北京:清华大学出版社,2015:107.
[20]李丽,牛奔.粒子群优化算法[M].北京:冶金工业出版社,2009:28.
[21]CHEN W,NGUYEN M,CHIU W,et al.Optimization of the plastic injection molding process using the taguchi method,RSM,and hybrid GA-PSO[J].The International Journal of Advanced Manufacturing Technology,2016,83(9/10/11/12):1873-1886.
[22]NA R,LI Q,WU L.An improved particle swarm optimization algorithm[J].Advanced Materials Research,2012,538/539/540/541:2658-2659.