摘要
针对国产9Ni钢镍基焊材熔敷金属强度和塑性不能同时达标问题,采用机器学习方法分析了Nb、Cr、Fe、Mn等合金元素与镍基焊材熔敷金属塑性和强度的相关性;又采用决策树模型研究了合金元素的浓度对镍基焊材熔敷金属塑性和强度的影响程度。研究发现:Nb元素在一定含量内可以提高熔敷金属的强度和塑性;Cr元素对熔敷金属的塑性有明显的提高作用。
The strength and plasticity of deposited metal of the nickel-based electrodes for 9Ni steel cannot meet the requirements at the same time.Aiming at this problem,the correlation between Nb,Cr,Fe,Mn,and the plasticity and strength of the deposited metal was analyzed by machine learning method.The decision tree model was used to study the effect of alloy element concentration on the plasticity and strength of the deposited metal.It is found that the Nb element can increase the strength and plasticity of the deposited metal in a certain content;the Cr element can significantly improve the plasticity of the deposited metal.
作者
董建涛
王帅
武钰栋
李洋
相茜
赵硕
罗震
Dong Jiantao;Wang Shuai;Wu Yudong;Li Yang;Xiang Qian;Zhao Shuo;Luo Zhen(Capital Aerospace Machinery Co.,Ltd.,Beijing 100076;School of Materials Science and Engineering,Tianjin University,Tianjin 300350;Chinese Mechanical Engineering Society,Beijing 100048)
出处
《航天制造技术》
2020年第3期11-14,19,共5页
Aerospace Manufacturing Technology
关键词
镍基焊条
LNG储罐
机器学习
决策树
nickel-based electrode
LNG carrier
machine learning
decision tree
