基于ANFIS方法的连续定向凝固BFe10-1-1合金的压缩流变应力模型  

Compressive flow stress model of BFe10-1-1 alloy fabricated by continuous unidirectional solidification process using ANFIS

作　　者：甘春雷[1] 刘雪峰[1] 黄海友[1] 谢建新[1] 

机构地区：[1]北京科技大学材料先进制备技术教育部重点试验室,北京100083

出　　处：《北京科技大学学报》2011年第5期600-605,共6页Journal of University of Science and Technology Beijing

基　　金：国家自然科学基金重点资助项目(No.50674008)

摘　　要：以连续定向凝固柱状晶组织BFe10-1-1合金在应变速率为0.01～10s^(-1)和变形温度为25～500℃条件下的压缩试验所得实测数据为基础,采用自适应神经网络模糊推理系统(ANFIS)方法,建立了连续柱状晶组织BFe10-1-1合金压缩变形真应力与变形温度、应变速率和真应变关系的预测模型.结果表明:ANFIS模型预测的流变应力值与试验值之间的平均误差为0.75%,均方根误差为2.13,相关系数为0.9996,很好地反映了实际变形过程的特征,而在相同情况下采用传统回归模型预测的平均误差为6.28%,表明ANFIS模型具有优良的预测精度.Based on the compression experimental data of BFe10-1-1 alloy with continuous unidirectionally solidified columnar grains, a prediction model for the relation of true stress to temperature, strain rate and true strain was developed using an adaptive network based fuzzy inference system （ANFIS）. The temperature at which the alloy was compressed was from 25 to 500 ℃ with the strain rate ranging from 0.01 to 10s^（-1）. Simulation results show that the mean percentage error, root mean square error and correlation coefficient between the ANFIS model and measured data of flow stress are 0.75%, 2.13 and 0.999 6, respectively, indicating that the ANFIS model can well reflect the real feature of the alloy during practical deforming process. In comparison with the regression model, whose mean percentage error is 6.28% under the same condition, ANFIS parades more accurate prediction performance for flow stress.

关 键 词：铜镍合金 压缩变形 柱状晶粒 流变应力 数学模型 自适应神经网络模糊推理系统 

分 类 号：TG115.5[金属学及工艺—物理冶金] TG146.1[金属学及工艺—金属学]