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A vision-based method for the broken spacer detection
Song YF(宋屹峰); Wang L(王林); Jiang Y(姜勇); Wang HG(王洪光); Jiang WD(姜文东); Wang CC(王灿灿); Chu JL(初金良); Han DF(韩东锋)
作者部门空间自动化技术研究室
会议名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议日期June 8-12, 2015
会议地点Shenyang, China
会议录名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码715-719
收录类别EI ; CPCI(ISTP)
EI收录号20161402187819
WOS记录号WOS:000380502300136
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
摘要Power line inspection is essential to the smooth running of the power grid. In the past, the power line inspection was mainly carried out manually, which means the liners had to inspect the power line in the field or watch the inspection video taken by UAVs or inspection robots. The manual inspection method is with disadvantages such as long time consumption and high manual labor cost. With the rapid growing of power grid, the demand for the power inspection has been continuously increased, but the manual inspection method can hardly meet the requirements for the power inspection due to its disadvantages. This paper presents a computer vision-based method for the broken spacer detection. The method is mainly implemented in three steps. First of all, the spacer is recognized in the region of interest. Secondly, the image morphology is used to extract the image feature. At last, we determine the broken spacer fault by the analysis of the connected domain in the image. Experimental results have successfully demonstrated the effectiveness of the proposed method.
语种英语
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17520
专题空间自动化技术研究室
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.Lishui Power Supply Company, State Grid, Lishui, China
3.Inspection and Maintenance Branch, Shanxi Electric Power Company, State Grid, Taiyuan, China
推荐引用方式
GB/T 7714
Song YF,Wang L,Jiang Y,et al. A vision-based method for the broken spacer detection[C]. Piscataway, NJ, USA:IEEE,2015:715-719.
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