A New Series Arc Fault Identification Method Based on Wavelet Transform

被引：0
|
作者：
Lu, Qiwei [1 ]
Wang, Tao [1 ]
He, Bangbang [1 ]
Ru, Tao [1 ]
Chen, Dawei [2 ]
机构：
[1] China Univ Min & Technol Beijing, Sch Mech Elect & Informat Engn, Beijing, Peoples R China
[2] Siemens Factory Automat Engn Ltd SFAE, Beijing, Peoples R China
来源：
IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2017年
关键词：
Series arc fault; wavelet transform; singular value decomposition; characteristic parameters; identification;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Series arc fault is an important incentive for electrical fires. Wavelet transform is a widely used series arc fault identification method. However, it is difficult to distinguish the normal condition and arc fault when only using wavelet transform, and a large amount of redundant data will be generated. To solve this problem, this paper presents a new series arc fault identification method which based on wavelet transform and singular value decomposition. The experiment platform was built according to UL1699, and the method was verified by experiments. The method presented in this paper can well distinguish the series arc fault and normal state. The accuracy of the series arc fault identification is high, and the redundant data is greatly reduced.
引用
收藏
页码：4817 / 4822
页数：6
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