小波变换
支持向量机
光伏系统
电弧故障断路器
计算机科学
可靠性(半导体)
小波
故障检测与隔离
离散小波变换
断层(地质)
电子工程
S变换
弧(几何)
傅里叶变换
模式识别(心理学)
人工智能
电压
工程类
功率(物理)
电气工程
短路
数学
物理
地质学
数学分析
机械工程
地震学
执行机构
量子力学
作者
Zhan Jie Wang,Robert S. Balog
标识
DOI:10.1109/pvsc.2016.7750271
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.
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