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Defect detection of bearing surfaces based on machine vision technique

机译:基于机器视觉技术的轴承表面缺陷检测

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Due to the high demands for productivity and quality of bearing and the shortage of traditional detection methods, this paper proposes an automatic detection system based on machine vision technique. The detection system uses digital image processing technology to process the images collected by CCD camera and finish identification for the surfaces of bearing quickly and accurately. Firstly, least squares fitting and annulus scan are used to locate the bearing and the regions which will be detected. Secondly, contrast enhancement and low-pass filtering are used to improve the quality of images. Next, object inspection is applied to determine whether defects exist. Finally, the shape feature is used to finish recognition of defects. Experiments show that the detection system has the features of high efficiency, high accuracy and ease of use. This research has a certain practical value.
机译:由于对轴承的生产率和质量的高要求以及传统检测方法的不足,本文提出了一种基于机器视觉技术的自动检测系统。该检测系统采用数字图像处理技术对CCD摄像机采集的图像进行处理,并快速,准确地完成对轴承表面的识别。首先,使用最小二乘拟合和环空扫描来定位轴承和将要检测的区域。其次,使用对比度增强和低通滤波来提高图像质量。接下来,应用对象检查来确定是否存在缺陷。最后,形状特征用于完成缺陷的识别。实验表明,该检测系统具有高效,高精度,易用的特点。该研究具有一定的实用价值。

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