| 高温合金的晶界提取及特征定量表征方法 |
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| 引用本文： | 刁福林,陈昊,李延丰,陈曦,杨立余.高温合金的晶界提取及特征定量表征方法[J].失效分析与预防,2019,14(1):23-29. |
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| 作者姓名： | 刁福林 陈昊 李延丰 陈曦 杨立余 |
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| 作者单位： | 南昌航空大学 信息工程学院,南昌330063;无损检测技术教育部重点实验室 (南昌航空大学) ,南昌330063;青岛啤酒股份有限公司,山东 青岛,266000;无损检测技术教育部重点实验室 (南昌航空大学) ,南昌,330063 |
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| 基金项目： | 国家自然科学基金;国家自然科学基金;江西省创新驱动工程优势学科创新团队计划项目;江西省优势科技创新团队项目;江西省自然科学基金;江西省图像处理与模式识别重点实验室开放基金;江西省高等学校教学改革研究项目 |
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| 摘 要： | 晶粒尺寸在金属的拉伸强度、韧性等力学性能方面起着决定性作用,为了定量评估金属中的晶粒,必须在金相图像中确定晶界。针对高温合金高倍显微图像中晶界模糊或断裂、析出相、抛光颗粒杂质干扰等现象,提出一种晶界提取的方法。通过拉普拉斯锐化和直方图均衡化等处理来增强图像对比度,再用Otsu法进行分割,将得到的晶界图求最大连通域去除独立的点,最后作平滑细化操作得到完整的晶界并计算出晶粒的特征参数。对GH4149、GH706、GH738金相图片进行处理,结果表明,该算法效果接近传统软件提取加人为后续加工的效果,省去了重复工作,具有一定的可靠性。
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| 关 键 词： | 晶界 边缘检测 特征参数 定量评估 |
| 收稿时间： | 2018-11-05 |
Study on Grain Boundary Extraction of Alloy Materials and Its Quantitative Evaluation Method |
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| DIAO Fu-lin,CHEN Hao,LI Yan-feng,CHEN Xi,YANG Li-yu.Study on Grain Boundary Extraction of Alloy Materials and Its Quantitative Evaluation Method[J].Failure Analysis and Prevention,2019,14(1):23-29. |
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| Authors: | DIAO Fu-lin CHEN Hao LI Yan-feng CHEN Xi YANG Li-yu |
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| Affiliation: | (Information Engineering College,Nanchang Hangkong University,Nanchang 330063,China;Key Laboratory of Nondestructive Test(Ministry of Education),Nanchang Hangkong University,Nanchang 330063,China;Tsingtao Brewery Company Limited,Shandong Qingdao 266000,China) |
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| Abstract: | The grainplay a decisive role in the tensile strength, toughness and other mechanical properties of the metal. In order to quantitatively evaluate the grains in the metal, the grain boundaries must be determined in the metallographic image. Aiming at the phenomenon of grain boundary blur or fracture, precipitated phase and interference of polished particles in high-power micrographs of high-temperature alloys, a method of grain boundary extraction proposed. mage contrast is enhanced by Laplacian sharpening and histogram equalization, and then segmented by Otsu method. The obtained grain boundary map is used to remove the maximum connected domain and the independent points are removed. Finally, the smoothing operation is completed to obtain some complete boundaries and the characteristic parameters of the grains are calculated. The metallographic images of GH4149, GH706 and GH738 are processed. The results show that the algorithm is close to the effect of traditional software extraction and subsequent processing, eliminating the need for repetitive work and reliability. |
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| Keywords: | grain boundaries edge detection characteristic parameters quantitative assessment |
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