基于磁光图像的飞机铆钉缺陷识别

针对飞机铆钉磁光图像的识别问题,提出了一种基于模糊支持向量机的裂纹有无和裂纹方向自动识别的新方法。该方法首先对铆钉磁光图像进行预处理得到铆钉二值化图像;然后采用阈值法求取铆钉中心;最后将由铆钉中心发出的星形射线矢量作为特征,采用模糊支持向量机方法对铆钉有无裂纹和裂纹方向进行分类。其中,支持向量机的核宽及惩罚常数采用网格法进行选取,并结合模糊隶属度函数解决多类分类问题中存在的错分和拒分现象。实验结果表明,使用训练获得的支持向量机分类器识别裂纹缺陷取得了很好的效果,能够满足自动检测的高实时性要求。

Defect Recognition of Aircraft Rivet Based on Magento-optic Image

Aiming at the magneto-optic image of aircraft rivet,a new automated recognition algorithm based on fuzzy support vector machine(FSVM)is presented in order to inspect the crack of rivet and its direction.The binary image of rivet is obtained by preprocessing the magneto-optic image;the approximate center of rivet is obtained through the threshold method;the star radial vector radiated from the approximate center of rivet is regarded as the characteristic,and the algorithm based on FSVM is used to inspect the crack of rivet and its direction.The kernel parameter and the penalty constant of SVM are optimized using the grid method.And fuzzy multi-class classification method is adopted to avoid refusal classification and false classification.Experiment results show that good effect of defect recognition is achieved using our SVM classifier,and the request of high real time in automated recognition is satisfied.