卫生陶瓷凝胶注模成型工艺的复杂性使其很难控制材料成型后的干燥收缩率,尝试用人工神经网络技术对卫生陶瓷凝胶注模成型工艺过程进行识别和仿真,采用Levenberg-Marquardt算法建立了卫生陶瓷凝胶注模成型工艺中单体、引发剂、交联剂、催化剂含量和坯体干燥收缩的映射网络模型,从而可利用该模型来预测在一定有机成型添加剂含量下卫生陶瓷的干燥收缩.结果表明,其预测平均误差小于0.65%,而且该模型可以分析任意2种工艺因素对陶瓷干燥收缩的偶合作用.
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