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基于图像处理的高体积分数SiC_(p)/Al复合材料ELID磨削表面质量评价

Evaluation of ELID Grinding Surface Quality of High Volume Fraction SiC_(p)/Al Composite Based on Image Processing
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摘要 对ELID磨削实验条件下的高体积分数SiC_(p)/Al复合材料工件表面进行了研究,通过扫描电镜(SEM)获取ELID磨削表面的形貌照片并进行观测,采用MATLAB软件对不同工件移动速度和不同磨削深度下的表面SEM照片进行灰度化、增强对比度、提取缺陷形状、降噪滤波以及将缺陷与平坦表面分割生成二值图像等处理,再通过ImageJ软件对图像中的缺陷进一步处理以获取相关数据,由此实现加工表面质量图像评价。结果表明:随着工件移动速度的增大,表面总体破坏程度变大,但大缺陷凹坑的尺寸变化不大,且凹坑数量在增加,所以表面质量变差;随着磨削深度的增加,表面总体破坏程度、大缺陷凹坑的尺寸和数量均在增加,表面质量变差。综上所述,高体积分数SiC_(p)/Al复合材料ELID磨削表面质量在较低工件移动速度和较小磨削深度下最好。 The surface of high volume fraction SiC_(p)/Al composites machined by ELID grinding experiment is studied.Scanning electron microscope(SEM)is used to observe the topography photos of ELID grinding surface,and MATLAB is used to realize the process of gray,enhance contrast,extract the shape of defects,reduce noise and filter,and segment defects and flat surfaces to generate binary images for SEM photos at different workpiece moving speeds and grinding depths.The defects in the image is further processed by ImageJ to obtain relevant data,etc.,so as to achieve the image evaluation of the processed surface quality.The results show that with the increase of the moving speed of the workpiece,the overall damage degree of the surface does not change much,and the size of large defect pits does not change much,but the number of pits is increasing,so the surface quality becomes worse.With the increase of grinding depth,the overall damage degree of the surface,the size and number of large defect pits are increasing,and the surface quality becomes worse.In conclusion,the ELID grinding surface quality of high volume fraction SiC_(p)/Al composite is the best at low workpiece moving speed and small grinding depth.
作者 梁亚楠 于晓琳 黄树涛 许立福 Liang Yanan;Yu Xiaolin;Huang Shutao;Xu Lifu(College of Mechanical Engineering,Shenyang Ligong University)
出处 《工具技术》 北大核心 2023年第8期48-52,共5页 Tool Engineering
基金 国家自然科学基金面上项目(50975184) 辽宁省特聘教授资助项目。
关键词 SiC_(p)/Al复合材料 表面形貌 图像处理 缺陷特征 表面质量 SiC_(p)/Al composite surface topography image processing defect feature surface quality
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