电气技术2024，Vol.25Issue(11)：10-14,21,6.
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
Research on parameters of fault region segmentation method for infrared images of substation based on K-means clustering
摘要
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.关键词
变电站/设备故障/红外图像/图像识别/K均值聚类Key words
substation/equipment fault/infrared image/image identification/K-means clustering引用本文复制引用
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):10-14,21,6.基金项目
湖南省自然科学基金(2024JJ6053) （2024JJ6053）
