摘要
以正交实验为基础,研究了连铸工艺条件中决定铸坯内外质量的铸造温度、冷却强度和引拉参数及其匹配,建立起成材率与主要工艺条件之间的神经网络描述,网络模型与遗传算法相结合对工艺条件的组合进行了优化,改善了铸坯的质量,提高了铸坯的成材率。
On the basis of the orthogonal experiments, the technical factors and combination such as casting temperature, cooling intensity as well as drawing conditions were studied in the casting process. The mapping model of artificial neural networks were built by using the data obtained from the orthogonal experiments. With the help of this mapping model, the optimal casting factors and conditions were investigated by simulating, GA optimization＇s method and real experiments. The results show that micro-structure of castings billet are improved and ratio of accepted products are enhanced.
出处
《热加工工艺》
CSCD
北大核心
2006年第1期37-39,共3页
Hot Working Technology
基金
山东省教育厅J00A08资助
关键词
水平连铸
H90带坯
神经网络
遗传算法
工艺条件
horizontal continuous casting
H90 alloy billet
artificial neural networks
genetic algorithms
technological factors
