59 / 2018-08-21 10:54:12

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

Ice-Covered Outdoor Insulator,Image Processing Method,Image Characteristic Extraction,Surface Phenomena,Flashover Monitoring

As one of the basic equipments in power system, the reliability of outdoor insulators is essential to the safe and stable operation. Due to the exposure to atmospheric conditions, various of climate parameters, such as icing, raining, wet-contamination, etc., should be considered seriously for enhancing the insulator operating performance. In recent years, one of the serious problems of outdoor insulators in many cold regions is the ice accretion, which can reduce the electrical performance and cause surface discharges, even the icing flashover. Therefore, it is necessary to investigae the discharge mechanism and performace evaluation of ice-covered outdoor insulators.
In this paper, in order to enhance the ability of judging the flashover risk of insulator in power system and reduce the ice flashover accident caused by ice-covered insulators, an image processing method was proposed to extract the characteristics of insulator surface phenomena for the flashover monitoring of ice-covered outdoor insulators. The experiments were carried out at CIGELE Laboratories to artifically make the wet-grown ice accretion on a 5-unit suspension ceramic insulator string. The procedures of icing accretion and flashover tests were in accordance with IEEE Std. 1783/2009. During the whole experiments, a high-speed video camera was applied to record the surface phenomena of the insualtor during both the ice accreting and flashover processes by using the recording rate of 6000 frames per second. The test was carried out at least 5 times under the determined experimental conditions.
Firstly, 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. Then, by using the direct equalization and gray stretch, the grayscale image of ice-covered insulator is enhanced to improve the image contrast and to sharpen the image edge. For the image noise, the wiener filtering and median filtering methodsare conducted for the noise reduction, which is a foundation for the further processing of ice-covered insulator images. Finally, the discharge images of ice-covered insulator during the flashover can be analyzed for the characteristic extraction based on the image processing method.
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 grey value and the arc length as the characteristic value for the flashover prediction. It can be found that the dynamic performance on the ice-covered insualtor can be visually reflected to reveal the initiation, propagation, extinguishment and re-ignition of surface discharges, which is related to different periods of the icing flashover process. 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 the 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 insulators.