基于机器视觉的滚抛磨块缺陷检测方法

为检测烧结型球状滚抛磨块的圆度和黑心缺陷，提出基于机器视觉的滚抛磨块缺陷检测方法。首先利用单片机、步进电机、采样圆盘、数字显微镜和上位机搭建磨块图像采集系统，实现磨块图像的连续采集；后利用图像灰度化、阈值分割、形态学处理提取磨块区域和黑心缺陷区域；再计算磨块区域的圆度和黑心缺陷尺寸；最后通过磨块缺陷检测试验确定磨块缺陷的检测阈值。结果表明:该方法能够对烧结型球状磨块的圆度和黑心缺陷进行数字化检测，分析磨块制备过程中存在的问题，为磨块制备方法改进提供反馈依据。 

Defect detection method of abrasive block based on machine vision

To detect the roundness and the black core defects of sintered spherical abrasive block, a defect detection method based on machine vision was proposed. Firstly, an image acquisition system of the abrasive block was built by using single chip microcomputer, stepping motor, sampling disc, digital microscope and upper computer to realize the continuous acquisition of the abrasive block images. Secondly, the image graying, the threshold segmentation and the morphological processing were used to extract the abrasive block area and the black core defect area. Thirdly, the roundness of the abrasive block area and the size of the black core defect were calculated. Finally, the detection threshold of the abrasive block defect was determined through the detection test. The results show that the method can digitally detect the roundness and the black core defects of sintered spherical abrasive block. It can also analyze the problems of in the preparation process of the abrasive block, thus providing feedback basis for the improvement of the abrasive block preparation method.