基于BP神经网络的钒基合金自蔓延高温合成工艺参数优化设计  

Process Optimization of Vanadium-based Alloy by Self-propagating High-temperature Synthesis Based on BP Neural Network

作　　者：李强[1] 许峰[1] 

机构地区：[1]安徽理工大学理学院,安徽淮南232001

出　　处：《热加工工艺》2013年第14期18-19,22,共3页Hot Working Technology

基　　金：安徽省自然科学研究项目(KJ2011Z105)

摘　　要：以坩埚H/D值、V2O5还原率、V2O5收得率、TiO2还原率和TiO2收得率为输入参数,钒基合金V3TiNi0.56收得率为输出参数,训练过程采用trainlm函数,设计了具有较高精确度的BP神经网络优化模型,可推广应用到各种钒基合金的自蔓延高温合成工艺参数的优化。Taking H/D value of pot crucible, reducing ratio of V205, yield of V205, reducing ratio of TiO2 and yield of TiO2 as input parameters and the yield of vanadium-based alloy V3TiNio as output parameters, trainlm function was used in training function. The optimization model can be applied to guide the practical process of self-propagating high-temperature synthesis for vanadium-based alloy.

关 键 词：BP神经网络 钒基合金 工艺优化 自蔓延高温合成 

分 类 号：TG146.413[一般工业技术—材料科学与工程] TP183[金属学及工艺—金属材料]