钢化玻璃绝缘子缺陷检测方法及装置研究

Development of the Method and Equipment of Defect Detection for Toughened Glass Insulator

介绍了一种新型的钢化玻璃绝缘子玻璃件缺陷检测方法及检测装置。在机器视觉技术的基础上，分析了绝缘子玻璃件缺陷及散射光带出现的统计学规律，采用旋转控制平台和环形大面积LED光源，利用Canny算子边缘检测图像分割技术，并运用人工神经网络分类器，克服了钢化玻璃绝缘子玻璃件形状的复杂性以及缺陷的多样性造成缺陷检测的困难。测试实验结果表明，该装置及其检测方法能够满足工业企业自动化生产的需要。

A new detection method and its equipment for defects of toughened glass insulators are described. The statistical law of distribution of glass insulator defects and hands of scattered light are analyzed. Based on machine vision technology, a large area ring LED light source is used in the rotary control platform. Canny operator image segmentation and neural network technology are presented in this research in order to overcome the difficulties in defect detections caused by complex shapes of toughened glass insulators and diversity of the defects. The experiment shows this method and equipment can meet the needs of industrial automation production.