基于神经网络的封接玻璃热膨胀系数研究  

Study on the thermal expansion coefficient of artificial neural networks used in sealing glass

作　　者：冯邻江[1,2] 王华[1,2] 饶立强 陈洁[1,2] 赵彦[1,2] 张立新[1,2] 鞠华[1,2] 

机构地区：[1]重庆材料研究院,重庆400707 [2]国家仪表功能材料工程技术研究中心,重庆400707 [3]北京环鼎科技有限责任公司,北京102200

出　　处：《功能材料》2012年第B11期262-265,共4页Journal of Functional Materials

基　　金：重庆市科技攻关资助项目(2011AC4205)

摘　　要：采用基于COM组件的混合编程技术编写了BP网络模型预测软件,并用该软件对封接玻璃SiO2-Al2O3-PbO-R2O系统的玻璃样品进行了热膨胀系数预测。预测结果表明,模型对给定组成玻璃热膨胀系数的预测值与实际测试值的相对误差在4%以内,该方法在对耐温耐压封接玻璃的配方设计中可起到重要作用。A predicted software of BP artificial neural network model was by created using of hybrid programming based on COM builder. The thermal expansion coefficient of glass samples which belongs to the SiO2- Al2O3-PbO-R2O glass system had been predicted by the predicted software . It is found that the relative error between the experiment value and predicted value is less than 4 %. The method have an important effect on formulation design of high-temperature-high-pressure sealing glass.

关 键 词：封接玻璃 热膨胀系数 BP网络 

分 类 号：TQ171[化学工程—玻璃工业]