金刚石与磨料磨具工程2017，Vol.37Issue(2)：31-35,40,6.DOI:10.13394/j.cnki.jgszz.2017.2.0007
基于尺度共轭梯度神经网络的TC4钛合金磨削烧伤预测
Burns prediction of TC4-Ti-alloy based on scaled conjugate gradient neutral networks
摘要
Abstract
In order to predict the degree of TC4 titanium alloy after high-speed cylindrical grinding,surface hardness is used to differentiate grinding burns of the workpiece based on surface hardness value change resulted by phase transformation after grinding burn.Surface hardness of TC4 titanium alloy after high-speed cylindrical grinding is forecasted using the scaled conjugate gradient algorithm of neural network.Correspondence relationship between the surface hardness value and the degree of grinding burn is used to predict grinding burns.Validation experiment indicates that the error between the experiments and the predictions is within 5 ％,which means that the model prediction effect is good.关键词
TC4钛合金/表面硬度/烧伤预测/共轭梯度法Key words
TC4 titanium alloy/surface hardness/burns prediction/conjugate gradient method分类
矿业与冶金引用本文复制引用
邓朝晖,肖蓝湘,邓辉,刘伟..基于尺度共轭梯度神经网络的TC4钛合金磨削烧伤预测[J].金刚石与磨料磨具工程,2017,37(2):31-35,40,6.基金项目
国家科技支撑计划课题“机床主轴和船舶凸轮轴智能制造的工艺软件和知识库研发(2015BAF23B01)” （2015BAF23B01）
湖南省研究生科研创新基金项目(CX2015B483). （CX2015B483）
