注射机实验系统注射过程能耗的研究
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摘要
注射成型是批量生产塑料制品的首选方法,在生产中得到广泛的应用,是塑料加工中重要的成型方法之一。塑料制品加工行业是国民经济各行业中近几年发展速度较快的行业之一,但注射机的能耗问题已经日益凸现。注射能耗问题的解决,关系着塑料制品加工行业的发展,关系着整个行业的前景。
本课题主要研究了注射机实验系统中,注射工艺参数与注射过程能耗的关系。
协助建立注射机实验系统,包括注射成型机、传感检测系统及数据采集系统,为课题研究奠定基础。提出以单产注射能耗作为能耗评价标准,并设计了正交试验来研究注射参数对单产注射能耗影响。通过分析得到各注射工艺参数对单产注射能耗的影响程度排序,并得到能使能耗相对降低的工艺参数组合。对于对注射能耗影响最大的3个参数——喷嘴温度、注射速度、保压压力分别进行单因素变动试验,分析各参数与注射功耗以及制品质量的关系,从而探讨各参数对单产注射能耗的影响。
应用神经网络对注塑工艺参数及其相对应的单产注射能耗样本进行训练,得到描述工艺参数到单产注射能耗映射关系的ANN模型,并通过实际的注射实验数据验证了此模型的准确性。通过ANN模型建立起了工艺参数与单产注射能耗的内在联系。使用神经网络模型结合小步长搜索法进行工艺参数优化,通过安排二次正交试验并利用神经网络模型的预测功能以及二次正交试验结果的级差分析,对通过传统的单次正交试验所得到的最优化注射成型工艺参数组合进行了进一步的优化,使能耗进一步降低。
本课题的研究取得了一些对生产实际具有一定指导意义的理论依据和具有参考价值的结论及实验数据,并为后续的研究工作打下了良好的基础。
Injection molding, a preferred method to produce the plastic products in batches, has become an important molding method in plastic processing. It has been experiencing a rapidly developing period, whereas the problem of energy consumption of injection molding machine are presented more and more obviously. Solving of this problem is related to the development of the whole plastic processing industry.
This thesis is mainly about the effect of injection parameters on the injection energy comsumption.
The injection molding machine experimental system including the injection molding machine, sensors system and data recording system is established with teachers, which settles the bedrock of the following researching work. Injection Energy Comsumption per Yield is considered as the evaluating standard of energy comsumption. Meanwhile, Taguchi orthogonal experiment is designed to study the effect of injection parameters on energy consumption. According to the analysis of its result, the ranking about the influences of various process parameters to energy consumption is reached and the optimized parameter combination is obtained to minimize theenergy consumption. The effect of various process parameters--nozzletemperature, ram velocity and packing pressure, which influence most on the energy comsumption in injection process, are discussed by single factor experiments. According to the analysis of the results, the relationships between each parameter and injection power cost as well as product mass are investigated so as to inquire the effects of various parameters on Injection Energy Comsumption per Yield.
Non-linear relationship between the injection process parameters and Injection Energy Comsumption per Yield is established through the artificial neural network which is trained by the training samples from Taguchi experiment and testified by the test samples from single factor experiments. The optimization of injection parameters is performed through the ANN Model and tiny increment scouting method. The secondary orthogonal experiment is arranged and its result is simulated by the ANN Model. According to the analysis of the result, the further-optimized parameter combination is obtained to further minimize the energy consumption.
In conclusion, here some elementary studies of the relationship between injection parameters and injection energy consumption of injection molding machine are proposed. It will make a good basis for further study in the future.
本课题主要研究了注射机实验系统中,注射工艺参数与注射过程能耗的关系。
协助建立注射机实验系统,包括注射成型机、传感检测系统及数据采集系统,为课题研究奠定基础。提出以单产注射能耗作为能耗评价标准,并设计了正交试验来研究注射参数对单产注射能耗影响。通过分析得到各注射工艺参数对单产注射能耗的影响程度排序,并得到能使能耗相对降低的工艺参数组合。对于对注射能耗影响最大的3个参数——喷嘴温度、注射速度、保压压力分别进行单因素变动试验,分析各参数与注射功耗以及制品质量的关系,从而探讨各参数对单产注射能耗的影响。
应用神经网络对注塑工艺参数及其相对应的单产注射能耗样本进行训练,得到描述工艺参数到单产注射能耗映射关系的ANN模型,并通过实际的注射实验数据验证了此模型的准确性。通过ANN模型建立起了工艺参数与单产注射能耗的内在联系。使用神经网络模型结合小步长搜索法进行工艺参数优化,通过安排二次正交试验并利用神经网络模型的预测功能以及二次正交试验结果的级差分析,对通过传统的单次正交试验所得到的最优化注射成型工艺参数组合进行了进一步的优化,使能耗进一步降低。
本课题的研究取得了一些对生产实际具有一定指导意义的理论依据和具有参考价值的结论及实验数据,并为后续的研究工作打下了良好的基础。
Injection molding, a preferred method to produce the plastic products in batches, has become an important molding method in plastic processing. It has been experiencing a rapidly developing period, whereas the problem of energy consumption of injection molding machine are presented more and more obviously. Solving of this problem is related to the development of the whole plastic processing industry.
This thesis is mainly about the effect of injection parameters on the injection energy comsumption.
The injection molding machine experimental system including the injection molding machine, sensors system and data recording system is established with teachers, which settles the bedrock of the following researching work. Injection Energy Comsumption per Yield is considered as the evaluating standard of energy comsumption. Meanwhile, Taguchi orthogonal experiment is designed to study the effect of injection parameters on energy consumption. According to the analysis of its result, the ranking about the influences of various process parameters to energy consumption is reached and the optimized parameter combination is obtained to minimize theenergy consumption. The effect of various process parameters--nozzletemperature, ram velocity and packing pressure, which influence most on the energy comsumption in injection process, are discussed by single factor experiments. According to the analysis of the results, the relationships between each parameter and injection power cost as well as product mass are investigated so as to inquire the effects of various parameters on Injection Energy Comsumption per Yield.
Non-linear relationship between the injection process parameters and Injection Energy Comsumption per Yield is established through the artificial neural network which is trained by the training samples from Taguchi experiment and testified by the test samples from single factor experiments. The optimization of injection parameters is performed through the ANN Model and tiny increment scouting method. The secondary orthogonal experiment is arranged and its result is simulated by the ANN Model. According to the analysis of the result, the further-optimized parameter combination is obtained to further minimize the energy consumption.
In conclusion, here some elementary studies of the relationship between injection parameters and injection energy consumption of injection molding machine are proposed. It will make a good basis for further study in the future.
引文
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[3]J.C.Viana,A.M.Cunha,N.Billon.The thermomechanical environment and the microstructure of an injection moulded polypropylene copolymer[J].Polymer,2002,43:4185-4196
[4]丁常楷,曹继华.聚碳酸酯厚壁制品的注射成型[J].中国塑料,2005,19(10):70-73
[5]田学军.PMMA注射成型工艺及优化[J].工程塑料应用,2005,33(8):22-24
[6]Wen Cao,Ke Wang,Qin Zhang,Rongni Du,Qiang Fu.The hierarchy structure and orientation of high density polyethylene obtained via dynamic packing injection molding[J].Polymer,2006,47:6857-6867
[7]杨其,王鹏驹,雷军,薛良,黄亚江.ABS注射成型收缩率的研究[J].工程塑料应用,2004(01).45-48
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[9]Prasad K.D.V.Yarlagadda,Cobby Ang Teck Khong,Development of a hybrid neural network system for prediction of process parameters in injection moulding[J],Journal of Materials Processing Technology,2001,Vol.118(1-3),109-115
[10]郭凤云,浅谈注射过程及工艺条件[J],质量天地,2002,Vol,05,61
[11]翟明,顾元宪,申长雨,注射成型充模过程的注射速度控制[J],中国塑料,2002,Vol.16(5),52-54
[12]王康正,张培仁,赵松,基于神经网络的注塑机注射速度的迭代学习控制[J],计算机辅助工程,2005,Vol.14(4),71-74
[13]李兆坚,常用塑料材料生命周期能耗计算分析[J],应用基础与工程科学学报,2006,Vol.14(1),40-49
[14]张友根,液压注塑机与电动注塑机共创注塑机的发展[A],PPTS2005塑料加工技术高峰论坛论文集[C],2005
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[16]王向东,杨惠娣.注塑成型技术进展[J].中国塑料,2001,Vol(10),1-6
[17]R.Spina,Injection moulding of automotive components:comparison between hot runner systems for a case study[J],Journal of Materials Processing Technology,Vo1.155-156,2004,1497-1504
[18]A.Demirer,Y.Soydan,A.O.Kapti,An experimental investigation of the effects of hot runner system on injection moulding process in comparison with conventional runner system[J],Materials & Design,In Press,Corrected Proof,Available online 6 May 2006
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