中国物理B ›› 2017, Vol. 26 ›› Issue (9): 98104-098104.doi: 10.1088/1674-1056/26/9/098104
• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇 下一篇
Yansu Hu(胡延苏), Zhijun Wang(王志军), Xiaoguang Fan(樊晓光), Junjie Li(李俊杰), Ang Gao(高昂)
Yansu Hu(胡延苏)1, Zhijun Wang(王志军)2, Xiaoguang Fan(樊晓光)2, Junjie Li(李俊杰)2, Ang Gao(高昂)3
摘要:
The mechanical properties of materials greatly depend on the microstructure morphology. The quantitative characterization of material microstructures is essential for the performance prediction and hence the material design. At present, the quantitative characterization methods mainly rely on the microstructure characterization of shape, size, distribution, and volume fraction, which related to the mechanical properties. These traditional methods have been applied for several decades and the subjectivity of human factors induces unavoidable errors. In this paper, we try to bypass the traditional operations and identify the relationship between the microstructures and the material properties by the texture of image itself directly. The statistical approach is based on gray level Co-occurrence matrix (GLCM), allowing an objective and repeatable study on material microstructures. We first present how to identify GLCM with the optimal parameters, and then apply the method on three systems with different microstructures. The results show that GLCM can reveal the interface information and microstructures complexity with less human impact. Naturally, there is a good correlation between GLCM and the mechanical properties.
中图分类号: (Phase diagrams and microstructures developed by solidification and solid-solid phase transformations)