基于机器视觉的滚动轴承外径检测系统

提出了一套基于机器视觉的滚动轴承外径检测方法。为了得到滚动轴承的有效外径信息，提出了一套边缘特征提取的算法。将边缘提取之后，进行最优中心检测。接着采用区域人工标定，进行滚动轴承外径的特征提取。然后，用主分量分析降低维度，得到滚动轴承外径的特征向量。最后，利用支持向量机进行分类，并将不合格的产品剔除，分类正确率达到了97％。

Rolling Bearing Outside Diameter Inspection System Based on Machine Vision

A rolling bearing outside diameter inspection method using support vector machine(SVM) was developed.To gain the effective outside diameter information of the rolling bearing,a sequence of image edge character distilling algorithms was developed.After edge was distilled,the optimal center inspection was implemented.Subsequently,the effective area was demarcated manually,and rolling bearing outside diameter character was distilled.Afterwards,principal component analysis(PCA) was applied to reduce the dimensional,and thus the character vector of the rolling bearing outside diameter was gained.Finally,SVM was used for classification of rolling bearing,and then the disqualification product was eliminated,and SVM resulted in the best classification accuracy with 97% on the test experiments.