A Vision-based method for the Broken Spacer Detection

被引：0

作者：

Song, Yifeng ^{[1
]}

Wang, Lin ^{[1
]}

Jiang, Yong ^{[1
]}

Wang, Hongguang ^{[1
]}

Jiang, Wendong ^{[2
]}

Wang, Cancan ^{[2
]}

Chu, Jinliang ^{[2
]}

Han, Dongfeng ^{[3
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110016, Peoples R China

[2] Lishui Power Supply Co State Grid, Lishui 323000, Peoples R China

[3] Shanxi Elect Power Co State Grid, Inspect & Maintenance Branch, Taiyuan 030000, Peoples R China

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER) | 2015年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

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.

引用

页码：715 / 719

页数：5

共 50 条

[11] Vision-Based Method for Forward Vehicle Detection and Tracking
Li, Xing
Guo, Xiaosong
2013 INTERNATIONAL CONFERENCE ON MECHANICAL AND AUTOMATION ENGINEERING (MAEE 2013), 2013, : 128 - 131
[12] Computer Vision-based Method for Concrete Crack Detection
Tran Hiep Dinh
Ha, Q. P.
La, H. M.
2016 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), 2016,
[13] Vision-based Contingency Detection
Lee, Jinhan
Kiser, Jeffrey F.
Bobick, Aaron F.
Thomaz, Andrea L.
PROCEEDINGS OF THE 6TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTIONS (HRI 2011), 2011, : 297 - 304
[14] Review of Research on Vision-Based Parking Space Detection Method
Ma, Yong
Liu, Yangguo
Shao, Shiyun
Zhao, Jiale
Tang, Jun
INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH, 2022, 19 (01)
[15] ON VISION-BASED ORIENTATION DETECTION METHOD OF RIGID-BODY
Niu, Fenglian
Chang, Qiuxiang
INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE & TECHNOLOGY, PROCEEDINGS, 2009, : 348 - 352
[16] A Machine Vision-Based Method of Impurity Detection for Rapeseed Harvesters
Chen, Xu
Guan, Zhuohuai
Li, Haitong
Zhang, Min
PROCESSES, 2024, 12 (12)
[17] A Vision-Based Method for Automatic Crack Detection in Railway Sleepers
Delforouzi, Ahmad
Tabatabaei, Amir Hossein
Khan, Muhammad Hassan
Grzegorzek, Marcin
PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2017, 2018, 578 : 130 - 139
[18] Vision-based obstacle detection method for outdoor mobile robot
Navigation Guidance and System Engineering Laboratory, College of Automation, Chongqing University, Chongqing 110004, China
不详
Jiqiren, 2009, 4 (304-310):
[19] A Drogue Detection Method for Vision-Based Autonomous Aerial Refueling
Song, Chunhua
Gao, Shibo
Cheng, Yongmei
MULTIMEDIA AND SIGNAL PROCESSING, 2012, 346 : 317 - 324
[20] Vision-Based Crowd Pedestrian Detection
Huang, Shih-Shinh
Chang, Feng-Chia
Liu, You-Chen
Hsiao, Pei-Yung
Ho, Hong-Fa
2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2015, : 878 - 881

← 1 2 3 4 5 →