Research on parameters of fault region segmentation method for infrared images of substation based on K-means clustering
XIAO Yi1,2, LI Weiqi3, WANG Yun3, HE Yushuang4, LUO Dan3
1. State Grid Chongqing Electric Power Company Yongchuan Power Supply Branch, Chongqing 402160; 2. State Grid Chongqing Electric Power Company Construction Branch, Chongqing 401100; 3. State Grid Chongqing Electric Power Company Shinan Power Supply Branch, Chongqing 401336; 4. School of Electrical & Information Engineering, Changsha University of Science and Technology, Changsha 410114
Abstract：This paper analyzed an fault region segmentation method for substation infrared images based on K-means clustering. Firstly, the principle of K-means clustering algorithm applied to image detection is introduced. Secondly, the fault region of infrared image is extracted by the K-means clustering algorithm, and the results show that the K-means clustering can be used for identification of fault region. Finally, the influence of K-means clustering algorithm parameters on infrared image segmentation is analyzed and discussed. The results show that the fault category and initial classification point of infrared image affect the accuracy of segmentation result. In practical application, the initial setting can be carried out according to the characteristics of infrared image to improve the efficiency and accuracy of image segmentation.
肖懿, 李伟绮, 王韵, 何渝霜, 罗丹. 基于K均值聚类的变电站红外图像故障区域分割方法参数研究[J]. 电气技术, 2024, 25(11): 10-14.
XIAO Yi, LI Weiqi, WANG Yun, HE Yushuang, LUO Dan. Research on parameters of fault region segmentation method for infrared images of substation based on K-means clustering. Electrical Engineering, 2024, 25(11): 10-14.
2024, Vol. 25 
