Image Processing Tool Quantifying Auto-Tempered Carbides in As-Quenched Low Carbon Martensitic Steels

被引：6

作者：

Babu, Shashank Ramesh ^{[1
]}

Davis, Thomas Paul ^{[2
]}

Haas, Tim ^{[3
]}

Jarvenpaa, Antti ^{[4
]}

Komi, Jukka ^{[1
]}

Porter, David ^{[1
]}

机构：

[1] Univ Oulu, Ctr Adv Steels Res, Mat & Mech Engn, Oulun 90014, Finland

[2] Univ Oxford, Dept Mat, Parks Rd, Oxford OX1 3PH, England

[3] Rhein Westfal TH Aachen, Dept Ind Furnaces & Heat Engn, Kopernikusstr 10, D-52074 Aachen, Germany

[4] Univ Oulu, Kerttu Saalasti Inst, Pajatie 5, FI-85500 Nivala, Finland

来源：

METALS | 2020年 / 10卷 / 02期

基金：

英国工程与自然科学研究理事会; 欧盟地平线“2020”;

关键词：

martensite; auto-tempering; image processing; quantification; carbides; MICROSTRUCTURES;

D O I：

10.3390/met10020171

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

As-quenched low-carbon martensitic steels (<0.2 wt.% C) contain auto-tempered carbides. Auto-tempering improves the work hardening and upper-shelf impact energy; however, an efficient characterization method to determine the degree of auto-tempering has not been available. This paper demonstrates an efficient image processing tool that calculates the relative auto-tempered carbide fraction by analyzing scanning electron microscope micrographs. By the process of image segmentation, the qualitative volume fraction of auto-tempered carbides can be determined, and an associated color map produced, which distinguished the levels of auto-tempering. This image processing tool could become useful for the optimization of new low-carbon steel's mechanical properties.

引用

页数：11

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