DocumentCode
1871155
Title
Research of low-voltage arc fault classification based on support vector machine
Author
Shuirong Liao ; Rencheng Zhang ; Yijian Huang ; He Xia
Author_Institution
College of Mechanical Engineering and Automation, Huaqiao University, Xiamen, Fujian, China
fYear
2012
fDate
3-5 March 2012
Firstpage
1690
Lastpage
1693
Abstract
Support vector machine is introduced into low-voltage arc fault research, carrying out arc fault classification analysis for different loads. Referring to U.S. UL1699 standard, current data is collected by doing experiment. Then support vector machine is used to classify and compare the recognition results for different kernels. Light bulbs, switching power and cleaner are selected as typical loads to analyze arc fault. The differences between normal arc and arc fault are compared. Finally, it is concluded that arc fault current is usually short-time zero, has big differences between positive and negative half-cycle, and has large variation of amplitude and other characteristics. This provides reference for further arc fault research.
Keywords
Matlab; Support vector machine; arc fault; electrical fire; low-voltage;
fLanguage
English
Publisher
iet
Conference_Titel
Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
Conference_Location
Xiamen
Electronic_ISBN
978-1-84919-537-9
Type
conf
DOI
10.1049/cp.2012.1311
Filename
6492918
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