Real-Time Image-Identification-Based Anti-Manmade Misoperation System for Substations

被引:14
作者
Cai, Wei [1 ]
Le, Jian [1 ]
Jin, Chao [2 ]
Liu, Kaipei [1 ]
机构
[1] Wuhan Univ, Sch Elect Engn, Wuhan 430072, Peoples R China
[2] Xiangyang Power Supply Bur, Xiangyang 441000, Peoples R China
基金
中国国家自然科学基金;
关键词
Anti-manmade misoperation; artificial neural network (ANN); Hough transformation; image identification; projection method; substation five-prevention system;
D O I
10.1109/TPWRD.2012.2190428
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A novel antimisoperation system is proposed to prevent manmade misoperations using real-time signboard image identification technology. A portable video capture device is employed to capture real-time images of the current working bay's substation signboard. These images, with the aid of image identification, are used to determine whether the operations staff has accessed a wrong bay. The framework and workflow of the system are provided, and the implementation of the signboard image border detection, character partition, and image-matching methods are also introduced in detail. The effectiveness and engineering applicability of the proposed system are demonstrated through lab results and in-field tests. The proposed system can be used in conjunction with an active five-prevention system to further improve the validity and safety of substation operations.
引用
收藏
页码:1748 / 1754
页数:7
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