挤出吹塑中型坯成型的神经网络模型的选取

型坯成型是挤出吹塑中的一个重要阶段,人工神经网络是一门新兴交叉科学.本文用几种不同的神经网络模型预测了挤出吹塑中型坯成型时的直径膨胀率,选取其中精度和效率均较高的模型,以用于下一步用神经网络来预测型坯成型时的壁厚膨胀率和最终制品的壁厚分布.     

挤出吹塑中型坯成型研究的进展

从理论研究和实验研究两个方面较为系统地介绍了挤出吹塑中型坯成型这一复杂阶段的研究现状 ,同时简要介绍了作者将神经网络方法应用于此阶段的研究工作     

基于神经网络的挤出吹塑中型坯尺寸预测

延续了本课题组在挤出吹塑中利用人工神经网络(ANN)预测型坯尺寸的工作,建立一个新的ANN模型。经过样本训练和检验后,模型能在一定范围内预测型坯任意位置上的尺寸(直径和厚度);与以往工作相比,相同的实验量能提供更丰富的训练样本。     

挤出吹塑中型坯成型的有限元模拟——型坯尺寸预测

建立了塑料挤出吹塑中平直型机头内非牛顿粘弹性熔体的流动模型，并利用POLYFLOW有限元软件进行求解，预测了不同型坯长度和不同流量时的型坯尺寸分布。     

挤出吹塑中型坯壁厚的调节

本文介绍了挤出吹塑中型坯壁厚的调节方法，包括轴向壁厚的程序控制与周向壁厚的调节（机头流道的异型化、ＳＦＤＲ法与ＰＷＤＳ系统）。     

塑料挤出吹塑的机理问题

采用不同的方法对挤出吹塑过程的型坯成型、型坯吹胀与制品冷却三阶段的机理问题进行了研究.采用人工神经网络方法预测了受模口温度和挤出流率影响的型坯成型阶段的膨胀.利用建立起来的神经网络模型预示的膨胀与实验结果很吻合,且可在一定范围内,预示不同工艺条件下型坯的直径膨胀和壁厚膨胀,为型坯的直径和壁厚的在线控制提供了理论依据.基于薄膜近似和neo-Hookean本构关系,建立了描述型坯自由吹胀的数学模型,并通过实验方法获得了型坯吹胀的瞬态图象.     

挤出吹塑型坯吹胀的CAD／CAE技术

对挤出吹塑型坯吹胀过程的CAD／CAE技术进行了初步研究。此技术可通过对吹塑CAD几何造型，CAD／CAE间信息传递，以及CAE分析的集成，实现对挤出吹塑型坯吹胀成型工艺过程的模拟和分析。最后用实例验证了此技术的可行性，为塑料制品的设计、材料选择、模具设计、吹塑成型工艺的制定及吹塑成型工艺过程的控制提供了科学依据。     

成功的产品开发有助降低吹塑产品成本

传统的吹塑工艺中，当两个相对的模瓣闭合在一起时，截断了一个挤出型坯之后，通过插入到闭合模具中的吹针引入压缩空气，使型坯膨胀。现在的挤出吹塑工艺在许多方面都作出改进，例如，共挤吹塑、3维吹塑和真空吹塑等，还有汽车零件，以单个的吹塑件替代原来独立的软管部件，配件和柔性连接件。     

挤出吹塑型坯吹胀的CAD/CAE技术

对挤出吹塑型坯吹胀过程的CAD／CAE技术进行了初步研究。此技术可通过对吹塑CAD几何造型，CAD／CAE间信息传递，以及CAE分析的集成，实现对挤出吹塑型坯吹胀成型工艺过程的模拟和分析。最后用实例验证了此技术的可行性，为塑料制品的设计、材料选择、模具设计、吹塑成型工艺的制定及吹塑成型工艺过程的控制提供了科学依据。     

挤出吹塑实验研究进展

对挤出吹塑过程的三个阶段：型坯成型、型坯吹胀以及制品冷却与固化阶段的实验方法和装置的研究现状进行了详细论述。     

New Strategies for Predicting Parison Dimensions in Extrusion Blow Molding

In this work, two new strategies were proposed for predicting the parison thickness and diameter distributions in extrusion blow molding. The first one was a finite-element-based numerical simulation for the parison extruded from a varying die gap. The comparison of simulated and experimental parison thickness distributions indicates that the new method has certain accuracy in predicting the parison thickness from a varying die gap. The second one was an artificial neural network (ANN) approach, the characteristics of which are in sufficient patterns that can be obtained without doing too many experiments. The diameter and thickness swells of the parisons extruded under different flow rates were obtained by a well-designed experiment. The obtained data were then used to train and test the ANN model. The dimension of one location on the parison can provide one pattern to train the ANN model. Trained and tested ANN model can be used to predict the dimensions at any location on the parison within a given range. The proposed two strategies can help search the processing conditions to obtain optimal parison thickness distributions.     

现代设计方法在型坯成型研究中的应用

系统地介绍了几种现代设计方法：有限元法、计算机辅助设计和人工神经网络方法；并阐述了几种现代设计方法在塑料挤出吹塑的型坯成型阶段中的应用现状。     

支持向量机在型坯挤出壁厚预测中的应用

将支持向量机应用于挤出吹塑过程的一段型坯壁厚分布的预测,并将预测结果与人工神经网络预测的结果进行比较,验证了支持向量机具有更强的泛化能力。     

挤出吹塑中型坯自由吹胀的动力学分析

聚合物挤出吹疗程 型坯的自由吹胀受到多方面因素的影响。采用动力学方法对此进行了研究。模拟了史胀过程听型坯轮廓变化， 吹胀压力，材料模量，型坯初始壁厚对此过程的影响。     

Modeling parison formation in extrusion blow molding by neural networks

A series of experiments were carried out on the parison formation stage in extrusion blow molding of high‐density polyethylene (HDPE) under different die temperature, extrusion flow rate, and parison length. The drop time of parison when it reached a given length and its swells, including the diameter, thickness, and area swells, were determined by analyzing its video images. Two back‐propagation (BP) artificial neural network models, one for predicting the length evolution of parison with its drop time, the other predicting the swells along the parison, were constructed based on the experimental data. Some modifications to the original BP algorithm were carried out to speed it up. The comparison of the predicted parison swells using the trained BP network models with the experimentally determined ones showed quite a good agreement between the two. The sum of squared error for the predictions is within 0.001. The prediction of the parison diameter and thickness distributions can be made online at any parison length or any parison drop time within a given range using the trained models. The predicted parison swells were analyzed. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 2230–2239, 2005     

Corotating twin-screw extrusion of poly(lactic acid) PLA/poly(butylene succinate) PBS/ micro-lamellar talc blends for extrusion blow molding of biobased bottles for alcoholic beverages

Extrusion blow molding is a well-established technology for the manufacture of fossil-based plastic bottles. The process is, however, still little used for the manufacture of bottles with a low environmental footprint, especially those based on bioplastic from renewable sources. In this context, the objective of this work is precisely the study and experimental design of poly(lactic acid) PLA/poly(butylene succinate) PBS/micro-lamellar talc compounds for the manufacturing of bioplastic bottles, basically for wine packaging. In particular, the design was carried out to ensure, primarily, an adequate processability of the bioplastic material in the blowing process. Second, the compound was loaded with different micro-lamellar talc content so as to achieve protection from the environmental factors, which is of paramount importance to ensure a long shelf-life to wine. The bio-derived polyester resins are very complex to transform, as they are subject to thermo-hydrolytic degradation phenomena during the processing of the polymer melt. Processability is further limited in the presence of high micro-lamellar talc content that increases the melt viscosity, thus making the material even more difficult to shape by extrusion blow molding. The experimental analysis involved the use of a co-rotating twin-screw extruder for the manufacture of the bioplastic compounds. The compounds were first subjected to thermo-rheological and physical characterization tests. Second, it was tested in the extrusion blow molding process. The experimental results have shown that blends based on bio-derived polyester resins can be adequately processed by extrusion blow molding, showing extremely stable rheological behavior both during the extrusion phase of the parison and the subsequent blowing process of the parison itself. These blends have, therefore, an interesting potential to be used as an alternative with a low environmental footprint to oil-based plastics in the production of wine bottles.