| COMPUTER VISION-BASED DETECTION AND STATE RECOGNITION FOR DISCONNECTING SWITCH IN SUBSTATION AUTOMATION | |
Chen, Hongkai ; Zhao, Xiaoguang; Tan, Min; Sun, Shiying
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| Source Publication | INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION
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| 2017 | |
| Volume | 32Issue:1Pages:1-12 |
| Subtype | Article |
| Abstract | State recognition in disconnecting switches is important during substation automation. Here, an effective computer vision-based automatic detection and state recognition method for disconnecting switches is proposed. Taking advantage of some important prior knowledge about a disconnecting switch, the method is designed using two important features of the fixed-contact facet of such disconnecting switches. First, the Histograms of Oriented Gradients (HOG) of the fixed-contact are used to design a Linear Discriminant Analysis (LDA) target detector to position the disconnecting switches and distinguish their loci against a usual cluttered background. Then a discriminative Norm Gradient Field (NGF) feature is used to train the Support Vector Machine (SVM) state classifier to discriminate disconnecting switch states. Finally, experimental results, compared with other methods, demonstrate that the proposed method is effective and achieves a low miss rate while delivering high performance in both precision and recall rate. In addition, the adopted approach is efficient and has the potential to work in practical substation automation scenarios. |
| Keyword | Computer Vision Substation Automation Disconnecting Switch State Recognition Histograms Of Oriented Gradients Norm Gradient Field |
| WOS Headings | Science & Technology ; Technology |
| DOI | 10.2316/Journal.206.2017.1.206-4624 |
| WOS Keyword | IDENTIFICATION |
| Indexed By | SCI |
| Language | 英语 |
| Funding Organization | National Natural Science Foundation of China(61271432 ; State Grid Science and Technology Project: the Research of Multimedia and Streaming Media Based on Machine Learning ; 61273337) |
| WOS Research Area | Automation & Control Systems ; Robotics |
| WOS Subject | Automation & Control Systems ; Robotics |
| WOS ID | WOS:000397167200001 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/14399 |
| Collection | 复杂系统管理与控制国家重点实验室_先进机器人 |
| Affiliation | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| First Author Affilication | Institute of Automation, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Chen, Hongkai,Zhao, Xiaoguang,Tan, Min,et al. COMPUTER VISION-BASED DETECTION AND STATE RECOGNITION FOR DISCONNECTING SWITCH IN SUBSTATION AUTOMATION[J]. INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION,2017,32(1):1-12. |
| APA | Chen, Hongkai,Zhao, Xiaoguang,Tan, Min,&Sun, Shiying.(2017).COMPUTER VISION-BASED DETECTION AND STATE RECOGNITION FOR DISCONNECTING SWITCH IN SUBSTATION AUTOMATION.INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION,32(1),1-12. |
| MLA | Chen, Hongkai,et al."COMPUTER VISION-BASED DETECTION AND STATE RECOGNITION FOR DISCONNECTING SWITCH IN SUBSTATION AUTOMATION".INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION 32.1(2017):1-12. |
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