郭志明1,2，李杰1,2，李爽1,2，刘敏1,2，刘永鑫1,2
1.内燃机可靠性国家重点实验室，山东 潍坊 261061；2.潍柴动力股份有限公司，山东 潍坊 261061
摘要：为提高铸件表面缺陷的识别效率，分析机器视觉在发动机铸件表面缺陷检测中的应用。分析铸件表面缺陷特征和图像降噪和分割技术，改进和优化传统算法，以中值滤波代替均值滤波进行图像降噪，采用阈值法进行图像分割；依据系统框架设计，选配合适设备，设计检测流程，开发检测软件。应用机器视觉技术检测铸件样件表面缺陷。结果表明：气孔、砂眼缺陷检测的准确率分别为93.6%和95.2%；相比传统的检测方法，机器视觉铸件表面缺陷检测方法准确性高、实用性和经济性好，可较好地适用于生产现场。
关键词：铸件表面缺陷；机器视觉检测；图像处理；边缘检测；图像分割
Abstract：In order to improve the recognition efficiency of casting surface defects, the application of machine vision in engine casting surface defect detection is studied. The characteristics of casting surface defects, image denoising and segmentation technology are studied. The traditional algorithm is improved and optimized. The median filter is used to replace the mean filter for image denoising, and the threshold method is used for image segmentation; according to the system framework design, select appropriate equipment, design detection process and develop detection software. The accuracy of the surface defect detection method of machine vision casting is verified by the actual detection of casting samples. The results show that the accuracy of the detection of air hole and sand hole defects is 93.5% and 95.3% respectively. Compared with the traditional detection methods, the machine vision detection method for surface defects of castings has high accuracy, good practicability and economy, and can be better applied to the production site.
Keywords:casting surface defect; machine vision detection; image processing; edge detection; image segmentation
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