摘要
简要分析了工艺参数对高能球磨法制备超细石英粉体的影响,采用正交试验和均匀实验研究了球磨法制备超细石英粉体的具体工艺试验方法,应用人工神经网络技术建立了粉体参数预测模型,利用遗传算法的全局搜索能力,优化了BP网络权值,从而完善了基于BP网络的石英粉体粒径预测模型.试验结果表明:该模型具有较高的精度,较好地实现了球磨法制备石英粉体的粒径预测,为工艺参数选择提供理论依据.
The paper analyzes the effect of technological parameters on manufacturing superfine quartz powder body by the method of high-energy ball, and studies the detail test methods based on the orthogonal experimental design and the uniformity experimental design. The paper applies the artificial neural network technology to establish the prediction model of the quartz powder body particle diameter, and optimizes the weight of BP neural network model by using the global search capability of Genetic Algorithm, and advances the prediction model of superfine quartz powder particle diameter. The experimental results show that the model is precise to predict the particle diameter. The technology will provide the theoretic guidance for further studying the technology parameters of manufacturing superfine quartz powder body.
出处
《材料科学与工艺》
EI
CAS
CSCD
北大核心
2007年第1期55-58,63,共5页
Materials Science and Technology
基金
中国博士后科学基金资助项目(20060400242)
关键词
超细石英粉体
高能球磨法
工艺参数
试验方法
BP神经网络
superfine quartz powder
high-energy ball mill
technology parameters
test method
BP neural network
