[1]赵尚程,张认成,杜建华,等.采用小波变换的光伏串联电弧故障检测[J].华侨大学学报(自然科学版),2017,38(1):7-12.[doi:10.11830/ISSN.1000-5013.201701002]
 ZHAO Shangcheng,ZHANG Rencheng,DU Jianhua,et al.Photovoltaic Series Arc Fault Detection Utilizing Wavelet Transform[J].Journal of Huaqiao University(Natural Science),2017,38(1):7-12.[doi:10.11830/ISSN.1000-5013.201701002]
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采用小波变换的光伏串联电弧故障检测()
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《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第38卷
期数:
2017年第1期
页码:
7-12
栏目:
出版日期:
2017-01-09

文章信息/Info

Title:
Photovoltaic Series Arc Fault Detection Utilizing Wavelet Transform
文章编号:
1000-5013(2017)01-0007-06
作者:
赵尚程 张认成 杜建华 杨凯 潘冷
华侨大学 机电及自动化学院, 福建 厦门 361021
Author(s):
ZHAO Shangcheng ZHANG Rencheng DU Jianhua YANG Kai PAN Leng
College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China
关键词:
光伏系统 小波变换 故障诊断 串联电弧 能量特征
Keywords:
photovoltaic systems wavelet transform fault diagnosis series arc energy feature
分类号:
TM501.2
DOI:
10.11830/ISSN.1000-5013.201701002
文献标志码:
A
摘要:
建立光伏系统电弧故障实验平台,利用光伏模拟器仿真不同天气环境下的光伏阵列,对光伏系统中串联电弧故障信号进行检测和分析.采用小波变换的方法对串联电弧故障信号进行特征频带提取,并利用移动时间窗方法统计信号在小波分解后的高频系数的能量值,用其表征电弧故障信号的杂乱度和混沌度.研究结果表明:该检测方法为快速准确地诊断串联电弧故障提供有效判据.
Abstract:
To detect and analyze the series arc faults in photovoltaic(PV)systems, an experimental platform was established to study the PV systems within the arcing fault, and to simulate different weather conditions by using PV simulator module. A wavelet transform analysis technique was utilized for extracting features of series arc faults in a certain frequency band. Meanwhile, a method of moving time window was applied to calculate the energy values of high-frequency coefficients derived from wavelet decomposition, which can be used to represent the chaotic and disordered degree of the arc fault signals. Experimental results showed the detection method can provide an effective criterion to distinguish series arc fault in PV system.

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备注/Memo

备注/Memo:
收稿日期: 2015-11-29
通信作者: 张认成(1961-),男,教授,博士,主要从事机电系统安全检测技术及仪器方向的研究.E-mail:phzzrc@hqu.edu.cn.
基金项目: 福建省产学合作科技重大项目(2012H6013); 福建省科技计划重点项目(2013H0028)
更新日期/Last Update: 2017-01-20