| 引用本文: | 王尧,韦强强,葛磊蛟,牛峰,李奎,张立.基于电弧电流高频分量的串联交流电弧故障检测方法[J].电力自动化设备,2017,37(7): |
| WANG Yao,WEI Qiangqiang,GE Leijiao,NIU Feng,LI Kui,ZHANG Li.Series AC arc fault detection based on high-frequency components of arc current[J].Electric Power Automation Equipment,2017,37(7): |
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| 摘要: |
| 通过分析典型负载下电弧电流高频分量在时域与频域表现出的不同特征，提出一种串联交流电弧故障检测方法。该方法利用电弧电流变化率与其有效值的比值以及6~12 kHz频段电流幅值这2个特征参量进行串联交流电弧故障识别；并利用负载启动电流持续时间远远小于电弧电流持续时间的特点，设定电弧故障检测时间阈值，降低负载启动过程对串联交流电弧故障检测的影响。试验结果表明，所提方法能够实现串联交流电弧故障的快速检测，对硬件要求相对较低，简便易行。 |
| 关键词: 电弧故障 高频分量 特征参量 故障识别 |
| DOI：10.16081/j.issn.1006-6047.2017.07.029 |
| 分类号:TM501+.2 |
| 基金项目:国家自然科学基金资助项目(51607055)；河北省自然科学基金资助项目(E2015202143)；河北省教育厅青年科学基金资助项目(QN2014148)；广东绿色能源技术重点实验室项目(2008A0-060301002) |
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| Series AC arc fault detection based on high-frequency components of arc current |
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WANG Yao1, WEI Qiangqiang1, GE Leijiao2, NIU Feng1,3, LI Kui1, ZHANG Li4
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1.Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin 300130, China;2.School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China;3.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;4.Zhejiang High and Low Voltage Electric Equipment Quality Inspection Center, Wenzhou 325603, China
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| Abstract: |
| The performance of high-frequency components of arc current with typical load in time domain is quite different from that in frequency domain, based on which, a detection method is proposed for series AC arc fault. The ratio of arc current variation rate to its RMS and the current amplitude of 6 kHz ~12 kHz band are used as the characteristic parameters to identify the series AC arc fault. Since the duration of load startup current is far shorter than that of arc current, the time threshold of arc fault is set accordingly to reduce the influence of load startup process on the arc fault detection. Test results show that the proposed method can easily realize the rapid detection of series AC arc fault with simple hardware. |
| Key words: arc fault high-frequency component characteristic parameter fault identification |
