Tian Hongzhi, Wang Dongxing, Lin Jiangang, Chen Qilin, Liu Zhaocai
School of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China.
Sensors (Basel). 2020 Aug 13;20(16):4531. doi: 10.3390/s20164531.
Currently, surface defect detection of stamping grinding flat parts is mainly undertaken through observation by the naked eye. In order to improve the automatic degree of surface defects detection in stamping grinding flat parts, a real-time detection system based on machine vision is designed. Under plane illumination mode, the whole region of the parts is clear and the outline is obvious, but the tiny defects are difficult to find; Under multi-angle illumination mode, the tiny defects of the parts can be highlighted. In view of the above situation, a lighting method combining plane illumination mode with multi-angle illumination mode is designed, and five kinds of defects are automatically detected by different detection methods. Firstly, the parts are located and segmented according to the plane light source image, and the defects are detected according to the gray anomaly. Secondly, according to the surface of the parts reflective characteristics, the influence of the reflection on the image is minimized by adjusting the exposure time of the camera, and the position and direction of the edge line of the gray anomaly region of the multi-angle light source image are used to determine whether the anomaly region is a defect. The experimental results demonstrate that the system has a high detection success rate, which can meet the real-time detection rEquation uirements of a factory.
目前，冲压磨削平面零件的表面缺陷检测主要通过肉眼观察来进行。为了提高冲压磨削平面零件表面缺陷检测的自动化程度，设计了一种基于机器视觉的实时检测系统。在平面光照模式下，零件的整个区域清晰且轮廓明显，但微小缺陷难以发现；在多角度光照模式下，零件的微小缺陷能够被凸显出来。针对上述情况，设计了一种将平面光照模式与多角度光照模式相结合的光照方法，并通过不同的检测方法自动检测五种缺陷。首先，根据平面光源图像对零件进行定位和分割，并根据灰度异常检测缺陷。其次，根据零件表面的反射特性，通过调整相机的曝光时间将反射对图像的影响降至最低，并利用多角度光源图像灰度异常区域的边缘线位置和方向来确定异常区域是否为缺陷。实验结果表明，该系统具有较高的检测成功率，能够满足工厂的实时检测要求。
