碳纤维复合芯导线X射线图像标准化增强与缺陷检测方法  

Standardized Enhancement and Detection of Defects in X-Ray Images of Carbon Fiber Composite Core Wires

作　　者：陈大兵 魏寒来 胡轶宁 舒华忠[3] 王征 CHEN Dabing;WEI Hanlai;HU Yining;SHU Huazhong;WANG Zheng(Electric Power Research Institute,State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing,211103,China;School of Cyber Science and Engineering,Southeast University,Nanjing,210096,China;School of Computer Science and Engineering,Southeast University,Nanjing,210096,China)

机构地区：[1]国网江苏省电力有限公司电力科学研究院,南京211103 [2]东南大学网络空间安全学院,南京210096 [3]东南大学计算机科学与工程学院,南京210096

出　　处：《数据采集与处理》2020年第4期739-744,共6页Journal of Data Acquisition and Processing

基　　金：国家电网有限公司科技(5200-201918120A)资助项目。

摘　　要：碳纤维复合芯导线能够大幅度提高输电线路输送容量,但由于不耐弯折等原因导致多发断线,严重危害线路运行安全。为实现对长距离输电线路进行在线缺陷检测,本文提出了碳纤维复合芯导线缺陷自动检测方案。该方案首先对碳纤维复合芯导线的X射线图像进行图像成像标准化,进行了导线弯曲补偿和亮度一致化矫正,提高了数据的一致性,为导线自动化分析提供条件;然后利用深度卷积神经网络技术进行缺陷检测。以双层铝股线类型的碳纤维复合芯导线X射线图像作为研究对象进行实验,结果证明该方案可快速自动识别导线缺陷。Carbon fiber composite core wires can greatly increase transmission capacity of transmission lines.However,many breaks are caused due to the bending resistance and other reasons,which seriously endangers the safety of line operation.In order to realize on-line defect detection for long-distance transmission lines,this paper proposes an automatic defect detection scheme for carbon fiber composite core conductors.Firstly,the X-ray image of carbon fiber composite core conductors is standardized.Then,data consistency is improved to provide conditions for automatic analysis of conductors after bending compensation and brightness normalization.Finally,the deep convolution neural network technology is used for defect detection.Experiments on aluminum conductor composite core(ACCC)show that the scheme can quickly and automatically identify the defects of carbon fiber composite core conductors.

关 键 词：X射线成像 碳纤维复合芯导线 标准化 缺陷检测 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]