Evaluating Grinding Surface Roughness of Engineering Ceramics with Greyscale Information on Surface Images
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摘要: 为简单高效地预测和评估陶瓷磨削表面粗糙度与加工质量,提出一种基于表面图像灰度信息的新方法。通过实验优选确定亮度140、对比度42、饱和度24、锐度9为图像采集条件,并选取灰度均值μ和均方差σ作为描述表面粗糙度的灰度参数。对采集图像进行降噪、增强和灰质化等数字图像处理后,分别提取每6幅表面图像的灰度信息,建立表面粗糙度评定参数Ra、Rz、Ry与灰度信息平均值的关系模型。对该模型作深入分析后,得到μ和σ与陶瓷磨削加工表面粗糙度成正比例变化的结论,可用于快速评定多种陶瓷磨削后的表面粗糙度。Abstract: We propose a new method for evaluating and predicting the grinding surface roughness of engineering ceramics efficiently,using the grayscale information on their surface images.First,through experiments,we select luminance 140,contrast 42,saturation 24 and acutance 9 as the image-acquisition parameters and then select the mean value and mean square deviation of the grayscale as its parameters for describing the surface roughness.Second,after the acquired images receive the digital image processing of noise reduction,image enhancement and grey enhancement,we extract the grayscale information on every other 6 surface images to establish the model of the relationship between the surface roughness evaluation parameters Ra、Rz、Ry and the mean value of grayscale information.Finally,the analysis of the model shows that the mean value and mean square deviation of the grayscale are proportional to the grinding surface roughness;this conclusion can be used to quickly evaluate the surface roughness of various kinds of ceramics after grinding.
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[1] 田欣利,于爱兵.工程陶瓷加工的理论与技术[M].北京:国防工业出版社,2006 [2] 杨俊飞,田欣利,吴志远等.结构陶瓷材料加工技术的新进展[J].兵工学报,2008,29(10):1249~1255 [3] 袁长良,丁志华,武文堂.表面粗糙度及其测量[M].北京:机械工业出版社,1989 [4] 时小军,张玉琴,张小辉.基于机器视觉技术的研磨表面粗糙度检测[J].机械设计与研究,2010,26(3):101~107 [5] 冯建,周晨波,于文英等.基于灰度共生矩阵的表面粗糙度研究[J].光学与光电技术,2007,5(2):39~41 [6] 阮久忠,周晨波,杨国华等.基于灰度共生矩阵的非平面表面粗糙度的图像纹理研究[J].光学与光电技术,2008,6(6):36~40 [7] 李庆华,李振华.基于分形理论的表面粗糙度测量研究[J].长春大学学报,2010,20(4):47~49 [8] Gonzalez R C,Woods R E,Eddins S L著.阮秋琦等译.数字图像处理(第2版)[M].北京:电子工业出版社,2007 [9] 程应科,林滨,张光秀等.工程陶瓷磨削加工表面损伤图像检测[J].稀有金属材料与工程,2008,37(增刊1):116~119 [10] 章毓晋.图像处理(第2版)[M].北京:清华大学出版社,2006 [11] 李大勇,王文卓,石德全.基于数字图像处理的锻造表面粗糙度自动检测[J].铸造,2007,56(9):963~966 [12] 陈向伟,张志魁,刘兆会.基于计算机视觉表面粗糙度的自动测量方法[J].机床与液压,2010,38(10):70~72
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