TY - GEN
T1 - Contamination Identification and Classification on Composite Insulator by Visible Light Images
AU - Chen, Tian
AU - Li, Fan
AU - Wei, Zixiang
AU - Li, Zhaojing
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/6
Y1 - 2020/9/6
N2 - Pollution flashover occurs more easily on contaminated transmission line insulators, which causes huge losses to the power system. In order to prevent the pollution flashover, the first step is to identify the contamination grade of insulator. This paper identifies the pollution grade through the color characteristic of visible light image. Firstly, the image segmentation method based on the randomized Hough transform method is adopted to achieve the surfaces of the red composite insulators with different contamination grades in the transformer substations of Heilongjiang Power Grid. Then, a total of 36 kinds of characteristic of R,\ G,\ B,\ H,\ S and V component images are calculated. According to Fisher criterion, the mean and median of S component, which can significantly represent the contamination grade, are selected. Finally, a support vector machine for classification decision is designed. Experimental results show that the identification accuracy of the composite insulators reaches 97.5%, which proves this method can be used for identification of composite insulator contamination grade.
AB - Pollution flashover occurs more easily on contaminated transmission line insulators, which causes huge losses to the power system. In order to prevent the pollution flashover, the first step is to identify the contamination grade of insulator. This paper identifies the pollution grade through the color characteristic of visible light image. Firstly, the image segmentation method based on the randomized Hough transform method is adopted to achieve the surfaces of the red composite insulators with different contamination grades in the transformer substations of Heilongjiang Power Grid. Then, a total of 36 kinds of characteristic of R,\ G,\ B,\ H,\ S and V component images are calculated. According to Fisher criterion, the mean and median of S component, which can significantly represent the contamination grade, are selected. Finally, a support vector machine for classification decision is designed. Experimental results show that the identification accuracy of the composite insulators reaches 97.5%, which proves this method can be used for identification of composite insulator contamination grade.
KW - composite insulator
KW - contamination grade
KW - randomized Hough transform
KW - support vector machine
KW - visible image
UR - http://www.scopus.com/inward/record.url?scp=85099406482&partnerID=8YFLogxK
U2 - 10.1109/ICHVE49031.2020.9279771
DO - 10.1109/ICHVE49031.2020.9279771
M3 - Conference Proceeding
AN - SCOPUS:85099406482
T3 - 7th IEEE International Conference on High Voltage Engineering and Application, ICHVE 2020 - Proceedings
BT - 7th IEEE International Conference on High Voltage Engineering and Application, ICHVE 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE International Conference on High Voltage Engineering and Application, ICHVE 2020
Y2 - 6 September 2020 through 10 September 2020
ER -