Arc Fault and Flash Detection in Photovoltaic Systems Using Wavelet Transform and Support Vector Machines

被引：0
|
作者：
Wang, Zhan [1 ]
Balog, Robert S. [1 ]
机构：
[1] Texas A&M Univ, College Stn, TX 77843 USA
来源：
2016 IEEE 43RD PHOTOVOLTAIC SPECIALISTS CONFERENCE (PVSC) | 2016年
基金：
美国国家科学基金会;
关键词：
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Arc faults pose significant reliability and safety issues in today's photovoltaic (PV) systems. This paper presents an effective method based on wavelet transform and support vector machines (SVM) for detection of arc faults in DC PV systems. Because of its advantages in time-frequency signal processing, wavelet transform is applied to extract the characteristic features from system voltage/current signals. SVM is then used to identify arc faults. The performance of the proposed technique is compared with traditional Fourier transform based approaches.
引用
收藏
页码：3275 / 3280
页数：6
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