摘要
高压电缆终端漏油缺陷往往通过红外图像的方式进行检测,而人工评估既耗时又费力,因此通过图像处理算法对所采集的电缆终端红外图像进行自动计算,评估终端是否存在漏油缺陷。首先通过有限元算法分析漏油终端表面温度的特点,然后通过滤波算法对图像进行降噪预处理,并通过边缘提取算法对图像中的电缆终端进行图像区域分割,最后基于分割图像的灰度值曲线进行漏油评估。现场试验验证了所提图像处理方法的有效性。
Oil leakage defects of high-voltage cable terminals are often detected by infrared images,and manual evaluation is time-consuming and laborious.Therefore,in this paper,the infrared image of cable terminal is automatically calculated by image processing algorithm to evaluate whether there is oil leakage defect in the terminal.Firstly,the characteristics of the surface temperature of the oil leakage terminal are analyzed by finite element algorithm.Then,the image is denoised by filtering algorithm,and the image area of cable terminal in the image is segmented by edge extraction algorithm.Finally,the oil leakage is evaluated based on the gray value curve of the segmented image.The field experiment verifies the effectiveness of the proposed image processing method.
作者
宋伟
李昆晟
吴科
吴照国
何维晟
SONG Wei;LI Kunsheng;WU Ke;WU Zhaoguo;HE Weisheng(State Grid Chongqing Electric Power Company Cable Management Center,Chongqing 400021,China;State Grid Chongqing Electric Power Company Electric Power Research Institute,Chongqing 400022,China;Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《电工技术》
2022年第22期207-209,共3页
Electric Engineering
关键词
电缆终端
红外图像
漏油
边缘提取
cable terminal
infrared image
oil-leakage
edge extraction
