摘要
通过对球墨铸铁机械性能影响因素的分析 ,指出在一定的生产条件下 ,球墨铸铁的机械性能主要取决于组织、成分。利用Matlab中的NeuralNetworkToolbox仿真环境和BP模型算法建立了球墨铸铁机械性能的优化模型 ,详细论述了模型结构的设计、数据处理、网络初始化、训练与仿真的过程。
Analyzing the relationship between mechanical properties and influence factors, the paper points out that the mechanical properties of ductile cast iron depends on microstructure and chemical composition in certain production process. An optimal model of mechanical properties in ductile cast iron is set up based on Matlab neural network toolbox and BP model. The processing, namely the structure design, the data processing, the network initialization, the network training and simulation about the model, is introduced. The method plays an important role in improving the mechanical properties in ductile cast iron.
出处
《材料科学与工程学报》
CAS
CSCD
北大核心
2003年第4期546-549,共4页
Journal of Materials Science and Engineering
基金
甘肃工业大学科研发展基金资助项目
