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金属学报  2021, Vol. 57 Issue (12): 1595-1606    DOI: 10.11900/0412.1961.2020.00432
  研究论文 本期目录 | 过刊浏览 |
高碳钢连铸坯大区域C元素分布不均匀度
郭中傲1,2, 彭治强1,2, 柳前1,2, 侯自兵1,2()
1.重庆大学 材料科学与工程学院 重庆 400044
2.重庆大学 钒钛冶金及新材料重庆市重点实验室 重庆 400044
Nonuniformity of Carbon Element Distribution of Large Area in High Carbon Steel Continuous Casting Billet
GUO Zhongao1,2, PENG Zhiqiang1,2, LIU Qian1,2, HOU Zibing1,2()
1.College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China
2.Chongqing Key Laboratory of Vanadium-Titanium Metallurgy and New Materials, Chongqing University, Chongqing 400044, China
引用本文:

郭中傲, 彭治强, 柳前, 侯自兵. 高碳钢连铸坯大区域C元素分布不均匀度[J]. 金属学报, 2021, 57(12): 1595-1606.
Zhongao GUO, Zhiqiang PENG, Qian LIU, Zibing HOU. Nonuniformity of Carbon Element Distribution of Large Area in High Carbon Steel Continuous Casting Billet[J]. Acta Metall Sin, 2021, 57(12): 1595-1606.

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摘要: 

基于典型高碳钢铸坯低倍组织灰度图,引入标准差、差分盒维数和惯性矩,探讨一种大区域主要偏析元素(C)分布不均匀度定量表征的简易方法。结果表明:标准差、差分盒维数和惯性矩可以有效地综合表征C元素分布不均匀度;且等轴晶区C元素分布不均匀度高于柱状晶区,平均相差20.85%。对比发现,标准差主要基于灰度值统计特性,差分盒维数和惯性矩结合了灰度值统计信息和空间分布信息;并且差分盒维数具有尺度独立性,受灰度图尺寸和分辨率的影响较小,而惯性矩对微区C元素分布不均匀度变化会更加敏感。此外,标准差主要受到大型偏析点(> 1 mm2)影响,而差分盒维数和惯性矩主要受中型偏析点(0.1~1 mm2)影响。本工作可为高碳钢铸坯大区域C元素分布不均匀度的全面衡量及精细化质量评判提供新的参考方法。

关键词 偏析不均匀度低倍组织连铸高碳钢    
Abstract

High carbon steel is prone to macroscopic and semimacroscopic segregation. Segregation is a phenomenon that results in the nonuniformity of solute element distribution during solidification; segregation severely impacts the quality of the casting billet. Based on qualitative analysis (macroscopic quality rating) and relatively simple quantitative analysis (segregation index, mean square error), it is found that the accuracy of existing technologies is limited for determining the nonuniformity of carbon element distribution in large areas of cast high carbon steel billets; this causes difficulties while applying such existing technologies for the evaluation of large samples under actual steelworks usage conditions. Therefore, it is essential to study the nonuniformity of carbon element distribution to precisely evaluate and optimize the quality of high carbon steel. Based on the grayscale image of the casting blank macrostructure of typical high carbon steels (mass fraction of carbon = 0.7%), the standard deviation, differential box-counting, and moment of inertia are introduced to discuss simple methods for the quantitative characterization of the nonuniformity of the major segregation element (C) in large areas. Then, the validity of the characterization results was verified using statistical homogeneity and the near-equilibrium solidification model, and the similarities and differences of the three characterization methods were discussed. The results showed that the standard deviation, differential box-counting, and moment of inertia can effectively reflect the nonuniformity of carbon element distribution. Furthermore, the mean value of the nonuniformity of carbon element distribution in the equiaxed area was 20.85% higher than that in the columnar area. The standard deviation is mainly based on the statistical characteristics of the grayscale value, while differential box-counting and moment of inertia combine the grayscale value statistical and spatial distribution information on a grayscale image of the casting blank macrostructure. In addition, differential box-counting has scale independence, which is less affected by the size and resolution of the grayscale image; the moment of inertia is sensitive to the variation of the nonuniformity of carbon element distribution in the microregion. Finally, the standard deviation is mainly influenced by large segregation points (e.g., area larger than 1 mm2), while differential box-counting and the moment of inertia are mainly influenced by medium segregation points (e.g., area of 0.1-1 mm2 ). Therefore, the three characterization methods can be combined to comprehensively evaluate the nonuniformity of carbon element distribution in large areas of cast high carbon steel billets. This research can provide a new theoretical reference for comprehensively evaluating the nonuniformity of carbon element distribution in a large area and for the fine quality evaluation of cast high carbon steel billets.

Key wordssegregation    nonuniformity    macrostructure    continuous casting    high carbon steel
收稿日期: 2020-10-30     
ZTFLH:  TF777.3  
基金资助:国家自然科学基金委员会-中国宝武钢铁集团有限公司钢铁联合研究基金项目(U1860101)
作者简介: 郭中傲,男,1996年生,硕士生
图1  铸坯中心纵断面取样位置示意图
图2  差分盒维数算法示意图
图3  铸坯不同位置的低倍组织灰度图
图4  铸坯不同位置的低倍组织灰度曲面
图5  铸坯不同位置的灰度值标准差
图6  铸坯低倍组织1#试样lnN(r)-ln(1 / r)关系
图7  铸坯不同位置的差分盒维数(D)
Sample No.DR2
1#2.61770.9946
2#2.66220.9950
3#2.67860.9946
4#2.68200.9943
5#2.71400.9946
6#2.67910.9946
表1  不同位置的低倍组织灰度图的D及对应的拟合系数(R2)
图8  惯性矩表征微区C元素分布不均匀度示意图
图9  铸坯不同位置的惯性矩
图10  铸坯不同位置的灰度直方图
Sample No.H / %

Grayscale value in the range

of content tolerance

1#11.98[97,110]
2#9.76[103,116]
3#8.39[115,130]
4#7.35[121,136]
5#6.02[121,136]
6#7.33[118,133]
表2  灰度值在含量允许差范围内所占的权重比率(统计均匀度(H))
图11  统计均匀度与标准差、差分盒维数、惯性矩的关系
图12  液相中C的质量分数(CL)与固相体积分数(fs)的关系
图13  5#、6#位置I、II、III 3类偏析点的面积比
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