【摘要】 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。更多还原

【Abstract】 The mechanism of the three stages in precessing of plastics extruding blow molding was studied using different methods. Neural network method was used to investigate the parison swell affected by the die temperature and extrusion flow rate. The comparison of the experimentally determined parison swell of high density polyethylene with the predicted ones using the neural network model showed very agreement between the two. The parison swell can be predicted at different processing conditions from the neural network model. A mathematical model based on the thin membrane approximation and neo-Hookean constitutive relations was used to describe the parison free inflation.更多还原