【摘要】 收缩率的选取是决定大型浇注型聚氨酯弹性体(CPUE)模具设计是否成功的关键因素之一.以大量的实验为基础,系统地研究了各种工艺参数对大型聚氨酯弹性体制品收缩率的影响,并建立了制品的结构模型以及基于BP网的神经网络模型.通过对实验数据的学习,利用该神经网络模型可以实现以工艺参数为输入,制品收缩率为输出的大型聚氨酯弹性体收缩率的预测.预测结果和实验数据的对比表明此方法可以较为准确地对不同工艺条件下的弹性体收缩率进行预测,从而减少修模次数,降低生产成本.更多还原

【Abstract】 The selection of shrinkage is one of the critical fact or s in successful design for large casting polyurethane elastomer(CPUE) mold.Based on experiments, the influence of process parameters on shrinkage of large CPUE products was systematically studied.The structural model of the products and the neutral network based on BP were estabilished.Through the learning of experimen tal data,the neutral network model could be used to predict the shrinkage of lar ge CPUE by taking the process parameters as input and product shinkage as output .The comparison of prediction results and experiment data indicated that the shr inkage of CPUE at different process parameters could be predicted.Thus the numbe r of mold repairing and production cost could be reduced.更多还原