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COMPUTER VISION-BASED DETECTION AND STATE RECOGNITION FOR DISCONNECTING SWITCH IN SUBSTATION AUTOMATION
Chen, Hongkai; Zhao, Xiaoguang; Tan, Min; Sun, Shiying
Source PublicationINTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION
2017
Volume32Issue:1Pages:1-12
SubtypeArticle
AbstractState 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.
KeywordComputer Vision Substation Automation Disconnecting Switch State Recognition Histograms Of Oriented Gradients Norm Gradient Field
WOS HeadingsScience & Technology ; Technology
DOI10.2316/Journal.206.2017.1.206-4624
WOS KeywordIDENTIFICATION
Indexed BySCI
Language英语
Funding OrganizationNational 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 AreaAutomation & Control Systems ; Robotics
WOS SubjectAutomation & Control Systems ; Robotics
WOS IDWOS:000397167200001
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Document Type期刊论文
Identifierhttp://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
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
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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