摘要
电缆中间接头是电缆最容易发生故障的部位,施工缺陷易引发绝缘故障。本文提出一种图像处理方法检测电缆中间接头缺陷,针对外半导电层剥离不齐缺陷,通过K-means聚类算法获得像素长度,与实际长度进行比较,对长度进行判断。通过试验验证了该方法可智能判定是否存在电缆中间接头施工缺陷。
The cable intermediate joint is most prone to failure in the cable,and the construction defects can easily lead to insulation failure.In this paper,an image processing method was proposed to detect the defect of cable intermediate joint.Aiming at the defect of uneven peeling of outer semi-conductive layer,the pixel length was obtained by K-means clustering algorithm,and the length was judged by comparing with the actual length.Through experimental verification,the method was comfilmed have the abillty judge whether there is a construction defect of cable intermediate joint is judged intelligently.
作者
李简
邱宇霆
周慧彬
方春华
陈志
LI Jian;QIU Yuting;ZHOU Huibin;FANG Chunhua;CHEN Zhi(China Southern Power Grid,Zhongshan Power Supply Company,Zhongshan 528400,China;School of Electrical and New Energy,China Three Gorges University,Yichang 443000,China)
出处
《电工材料》
2025年第4期24-28,共5页
Electrical Engineering Materials
基金
南方电网公司科技项目(032000KK52220033)。
关键词
电缆中间接头
缺陷检测
外半导电层
剥离不齐
K-MEANS聚类算法
cable intermediate joint
defect detection
outer semi-conductive layer
uneven stripping
the K-means clustering algorithm
