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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