短间隙真空开关电弧图像边缘提取研究

Edge Extraction Algorithm for Vacuum Swithing Arc at Short-Gap

为了研究短间隙真空开关电弧燃烧及其热形态变化过程,通过图像视觉系统对电弧起弧、燃烧及熄灭过程中的电弧图像进行采集,阐述了该实验系统的组成,利用图像处理技术对电弧图像进行了预处理,并通过Prewitt、LOG和Canny五种微分算子的边缘提取和结果对比。结果表明:比较3种微分算子对电弧图像边缘提取的结果,Canny算子可得到连续性、完整性和准确性均符合控制要求的电弧边缘结果,为实现真空电弧的调控提供了技术基础。

Here,we addressed the combustion and the heat morphological changes of the vacuum switching arc at short—gap.The experimental set-up was briefly described,and a series of the vacuum arc images in different stages,such as the triggering,burning,and extinguishing of the arc,were acquired with an charge coupled device camera,and the images were processed.Extraction of the edge of the vacuum switching arc images were performed with three differential operators,including the operators of Prewitt,LOG,and Canny;and the results were analyzed and compared.Interesting finding was that Canny differential operator outperforms the other two operators,when it comes to a continuous,complete,and precise edge,required by the controlling and regulating of the vacuum switching arc.