摘要:
为提高微缺陷检测结果精度、提升机械加工零件外观质量,该文引进了机器视觉技术,以某机械生产制造单位为例,设计了一种针对零件表面微缺陷的全新检测方法。根据机器视觉技术的应用需求,搭建了集成工业相机、采集装置、照射光源等为一体的扫描装置,采集零件表面图像;对采集的原始图像进行均值滤波处理,去除图像中可能对缺陷区域的判别造成干扰的因素与噪声;采用阈值分割的方式,提取并划分机械加工零件表面的微缺陷区域;采用提取图像边缘算子的方法,计算零件表面原始图像与待检测图像之间的像素相关性,通过对零件表面微缺陷灰度性质点的匹配,完成检测方法的设计。通过对比实验证明:该方法不仅可以精准检测机械加工零件表面微缺陷,还可以检测到具体的缺陷类别。
Abstract:
In order to improve the precision of micro-defect detection results and improve the appearance quality of machined parts, the machine vision technology is introduced in this paper. Taking a mechanical manufacturing unit as an example, a new technical method for micro-defects on the surface of parts is designed. According to the application requirements of machine vision technology, a scanning device integrating industrial camera, acquisition device and illumination light source is built to collect the surface image of parts. The collected original image is processed by mean filtering to remove the interference of relevant factors and noise in the image on identification of the defect areas. The method of threshold segmentation is adopted to extract and divide the micro-defect areas on the surface of machined parts. The method of extracting image edge operator is used to calculate the pixel correlation between the original image of the part surface and the image to be detected, and design of the detection method is completed by matching the gray nature points of the part surface micro-defects. The comparative experimental results show that this method can not only accurately detect the surface micro-defects of machined parts, but also detect the types of defects.
百度学术
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