电工技术学报  2022, Vol. 37 Issue (7): 1866-1874    DOI: 10.19595/j.cnki.1000-6753.tces.210307
高电压与放电 |
SF6放电的发射光谱特性分析与放电识别
李彦飞1,2, 汤贝贝1,2, 韩冬1,2, 邱宗甲1, 张国强1,2
1.中国科学院电工研究所 北京 100190;
2.中国科学院大学 北京 100049
Spectroscopy Analysis of Emission Spectrum Characteristics and Discharge Recognition of SF6 Gas Discharge
Li Yanfei1,2, Tang Beibei1,2, Han Dong1,2, Qiu Zongjia1, Zhang Guoqiang1,2
1. Institute of Electrical Engineering Chinese Academy of Sciences Beijing 100190 China;
2. University of Chinese Academy of Sciences Beijing 100049 China
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摘要 该文通过实验模拟六氟化硫(SF6)气体绝缘电气设备的三种常见放电缺陷(电晕放电、火花放电以及沿面放电),并采用光谱仪检测上述放电缺陷下的200~1 037nm波段范围内的发射光谱。结果表明,电晕放电的发射光谱主要由带状光谱(OH自由基谱带,SF6和SFx分子谱带)和微弱的F原子线状谱组成;火花放电的发射光谱在电晕放电的基础上新增了硫原子、硫离子和氟离子的线状光谱;沿面放电的发射光谱与火花放电的轮廓相似,但由于沿面故障模拟模型中引入了铜元素,因此发射光谱中出现了铜原子和铜离子的线状谱。最后,根据电晕放电、火花放电和沿面放电的光谱特性差异,定义了两个特征物理量:Iratio和|Inor(323.371nm)|,设计相应的放电识别算法。该算法的正确率为94.33%,可有效地识别实验中的SF6放电缺陷。
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韩冬
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张国强
关键词 六氟化硫(SF6发射光谱特征光谱局部放电放电识别    
Abstract:This paper simulated three common discharge defects of sulfur hexafluoride (SF6) gas insulated electrical equipment (corona discharge, spark discharge, and creeping discharge), and a spectrometer was used to detect the emission spectrum in the range of 200~1 037nm. The results show that, the emission spectrum of the corona discharge is mainly composed of band spectrum (OH radical band, SF6 and SFx molecular band) and weak line spectrum of fluoride atom; On the basis of corona discharge, the emission spectrum of the spark discharge has newly added linear spectra of sulfur atom, sulfur ion and fluoride ion; the outline of the emission spectrum under the creeping discharge is similar to the spark discharge. However, due to the introduction of copper in the creeping discharge, the linear spectra of copper atom appear in the emission spectrum. Finally, according to the difference in the spectral characteristics of the corona discharge, spark discharge and creeping discharge, this paper defines two characteristic physical quantities: Iratio and|Inor(323.371nm)|, and designs the corresponding discharge recognition algorithm. The accuracy of the algorithm is 94.33%, which can effectively identify SF6 discharge defects in the experiment.
Key wordsSulfur hexafluoride(SF6)    optical emission spectroscopy    characteristic spectrum    partial discharge    discharge recognition   
收稿日期: 2021-03-05     
PACS: TM855  
基金资助:国家自然科学基金(51877203)和中国科学院科研仪器设备研制项目(YJKYYQ20200012)资助
通讯作者: 韩冬 女,1975年生,副研究员,硕士生导师,研究方向为电力设备在线监测与故障诊断。E-mail:donghan@mail.iee.ac.cn   
作者简介: 李彦飞 男,1995年生,硕士研究生,研究方向为电力设备在线监测与故障诊断。E-mail:liyf@mail.iee.ac.cn
引用本文:   
李彦飞, 汤贝贝, 韩冬, 邱宗甲, 张国强. SF6放电的发射光谱特性分析与放电识别[J]. 电工技术学报, 2022, 37(7): 1866-1874. Li Yanfei, Tang Beibei, Han Dong, Qiu Zongjia, Zhang Guoqiang. Spectroscopy Analysis of Emission Spectrum Characteristics and Discharge Recognition of SF6 Gas Discharge. Transactions of China Electrotechnical Society, 2022, 37(7): 1866-1874.
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https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.210307          https://dgjsxb.ces-transaction.com/CN/Y2022/V37/I7/1866