Image Characteristic Extraction of Surface Phenomena for Flashover Monitoring of Ice-Covered Outdoor Insulator

In order to enhance the ability of judging the flashover risk of ice-covered insulators in power system, an image processing method was proposed to extract the characteristics of ice-covered outdoor insulator surface phenomena for the flashover monitoring. In view of the ice and discharges at the scene of the high image noise and the background of fuzzy characteristics, the weighted average method of image gray level was selected for the image pre-processing. The grayscale image of ice-covered insulator is enhanced to improve the image contrast and to sharpen the image edge by using the gray stretch. For the image noise, the mean filtering method conducted for the noise reduction. Based on the image processing method, the discharge images of ice-covered insulator during the flashover can be analyzed for the characteristic extraction. As different characteristics can be found for the discharge characteristics of ice-covered insulator under different conditions, the flashover process of ice-covered insulator can be divided into stages to extract the image gray value and the arc length as the characteristic value for the flashover prediction. In addition, the quantitative analysis of GI (the ratio of total gray value to length of image) and LI (the ratio of length of surface charge arc to length of image) were put forward as the risk value of ice-covered insulator flashover. Once GI and LI values exceed the threshold value, the higher flashover risk of ice-covered insulator can be obtained. The proposed monitoring methods will be helpful to evaluate the most hazards of ice-covered outdoor insulator.