摘要
使用一种基于Python语言的图像处理技术,对泡沫金属孔隙的横截面积、孔穴棱边周长、费雷特直径、孔隙形态等参数进行精确表征,实现对泡沫金属图像的相对密度批量化计算及输出。检测结果精确到了0.001,对单个孔隙进行特征表征只需0.0085 s,较传统方法缩短了82.3545 s,对146个孔隙进行特征表征只需1.241 s。
An image processing technology based on Python language was applied to accurately characterize parameters such as the cross-sectional area,hole edge circumference,Ferret diameter and pore morphology of metal foam pores,so as to achieve mass calculation and output of the relative density of metal foam images.The detection result is accurate to 0.001.It takes only 0.0085 s to characterize a single pore,which increases the detection efficiency by 82.3545 s compared with the traditional method,and takes only 1.241 s to characterize 146 pores.
作者
达文豪
王录才
王艳丽
游晓红
黄闻战
王芳
Da Wenhao;Wang Lucai;Wang Yanli;You Xiaohong;Huang Wenzhan;Wang Fang(School of Material Science and Technology,Taiyuan University of Science and Technology;School of Materials Science and Engineering,North University of China)
出处
《特种铸造及有色合金》
CAS
北大核心
2023年第8期1041-1048,共8页
Special Casting & Nonferrous Alloys
基金
山西省重点研发资助项目(高新技术)(201803D121004)
山西省高等学校教学改革创新资助项目(201901d111270)
山西省自然科学基金资助项目(201901d111270)。
关键词
泡沫金属
表征分析方法
图像处理
Metal Foam
Characterization Analysis Method
Image Processing
