摘要
通过分析C-Mn系冷镦钢的化学成分与机械性能之间的相关性,以指导材料设计和生产优化。基于251个样本数据,包括氮含量、氧含量、锰碳比(Mn/C)、碳当量(Ceq)等成分变量,以及硬度、伸长率、屈服强度、抗拉强度等性能变量,采用Python编程计算皮尔逊相关系数矩阵。结果表明,碳含量与抗拉强度呈正相关(相关系数0.380),碳当量与抗拉强度呈正相关(0.415),而氮含量与伸长率呈负相关(-0.286)。数据分布通过直方图展示,各变量分布基本符合正态分布,支持相关性分析。研究为C-Mn系冷镦钢的成分优化提供了数据支持,有助于提高产品质量和生产效率。
The aim of this study is to analyze the correlation between the chemical composition and mechanical properties of C-Mn cold heading steel,in order to guide material design and production optimization.Based on 251 sample data,including compositional variables such as nitrogen content,oxygen content,manganese carbon ratio(Mn/C),carbon equivalent(Ceq),as well as performance variables such as hardness,elongation,yield strength,and tensile strength,the Pearson correlation coefficient matrix was calculated using Python programming.The results showed that carbon content was positively correlated with tensile strength(correlation coefficient 0.380),carbon equivalent was positively correlated with tensile strength(0.415),while nitrogen content was negatively correlated with elongation(-0.286).The data distribution is displayed through a histogram,and the distribution of each variable basically conforms to a normal distribution,supporting the reliability of correlation analysis.This study provides data support for the composition optimization of C-Mn cold heading steel,which helps to improve product quality and production efficiency.
作者
樊尧桂
刘逖
卢广义
郭福建
张晗
Fan Yaogui;Liu Ti;Lu Guangyi;Guo Fujian;Zhang Han(Yangchun New Iron And Steel Co.,Ltd,Yangchun 529629,China;Yangjiang Advanced Materials Laboratory,Yangjiang 529500,China)
出处
《冶金信息导刊》
2026年第1期24-28,共5页
Metallurgical Information Review
关键词
C-Mn系冷镦钢
相关性分析
皮尔逊相关系数
成分优化
机械性能
C-Mn series cold heading steel
correlation analysis
pearson correlation coefficient
composition optimization
mechanical properties
