期刊文献+

电负性气体对局部放电特性的影响 被引量:11

Effect of Electronegative Gas on Partial Discharge Characteristics
下载PDF
导出
摘要 电负性气体的存在会对局部放电过程产生重要影响,为此,以低密度聚乙烯薄膜内的人工气隙作为研究对象,研究了不同氧气与氮气比例、不同湿度等条件对局部放电特性的影响,得到了不同气体成分和湿度条件下气隙中局部放电的谱图及放电量随时间变化的关系。研究表明,虽然同为电负性气体,但气隙中平均放电量随O2、N2混合气体中O2的体积分数的增加而减小,随湿度(H2O)的增加而增大,这是由于电负性气体对自由电子的吸附作用与附着电子在电压作用下的释放过程相互竞争决定的。兔形谱图与电负性气体无关,可能与N2有关,在气隙中气体为纯N2时,实验中容易出现兔形谱图;在气隙中湿度很高时,实验中容易出现类似正弦曲线形状的谱图,并对这些现象做出了分析和解释。 The process of partial discharges(PDs) will be affected by electronegative gas.Using the void inside low density polyethylene (LDPE) as the object,we focused on the change of the partial discharge characteristics with the electrical aging time,and also on the effects of the partial pressure ratio of O2 and N2 as well as the humidity.The experimental results show the mean partial discharge magnitude decreases with the increase of the mixture proportion of O2,and increase with the increase of humidity.This can be recognized as the interaction of the effect of attachment of the electronegative gas as well as the release of the attached electron through the electrical field.The rabbit like patterns show easily when the void is filled with pure N2,it is considered that the electronegative gas has no inevitability with the conformation of the rabbit like patterns.And the sine-shaped like patterns show easily when the humidity is high.This phenomenon is explained.
出处 《高电压技术》 EI CAS CSCD 北大核心 2010年第6期1372-1378,共7页 High Voltage Engineering
基金 国家自然科学基金(50677052) 国家教育部博士基金(20060698003)~~
关键词 人工气隙 局部放电 电老化 Φ-q-n谱图 电负性气体 平均放电量 voids partial discharge electrical aging Ф-q-n patterns electronegative gas the mean partial discharge magnitude
  • 相关文献

参考文献15

  • 1张仁豫.高电压实验技术[M].北京:清华大学出版社,2003.
  • 2杨霁,李剑,孙才新,王有元,杨眉.基于小波多尺度变换的局部放电图像识别方法[J].电力系统自动化,2005,29(22):64-67. 被引量:8
  • 3谈克雄,朱德恒,王振远,曾冬松.基于人工神经网络的局部放电识别[J].高电压技术,1996,22(1):21-24. 被引量:16
  • 4张毅刚,郁惟镛,赵亚奎.发电机绝缘诊断专家系统的研究[J].高电压技术,2004,30(9):35-37. 被引量:6
  • 5Abdel-Galil T K, Hegazy Y G, Salama M M A, et al. Partial discharge pulse pattern recognition using hidden Markov models [J]. IEEE Trans on Dielectrics and Electrical Insulation, 2004, 11(4): 715-723.
  • 6Candela R, Mirelli G, Schifani R. PD recognition by means of statistical and fractal parameters and a neural network [J]. IEEE Trans on Dielectrics and Electrical Insulation, 2000, 7 (1) : 87-94.
  • 7Cavallini A, Montanari G C, Puletti F. A fuzzy logic algorithm to detect electrical trees in polymeric insulation systems[J]. IEEE Trans on Dielectrics and Electrical Insulation, 2005, 12 (6) : 1134-1144.
  • 8Krivda A. Automated recognition of partial discharges[J]. IEEE Trans on Dielectrics and Electrical Insulation, 1995, 2 (5) : 796-821.
  • 9Hudon C, Bartnikas R, Wertheimer M R. Spark-to-glow discharge transition due to increased surface conductivity on epoxy resin specimens [J].IEEE Trans on Electrical Insulation, 1993, 28(1): 1-8.
  • 10Morshuis P H F. Degradation of solid dielectrics due to internal partial discharge: some thoughts on progress made and where to go now[J]. IEEE Trans on Dielectrics and Electrical Insulation, 2005, 12(5): 905-913.

二级参考文献8

  • 1CANDELA R,MIRELLI G,SCHIFANI R.PD Recognition by Means of Statistical and Fractal Parameters and a Neural Network.IEEE Trans on Dielectrics and Electrical Insulation,2000,7(1):87-94.
  • 2HANS-GERD K.Diagnosis of Partial Discharge Signals Using Neural Networks and Minimum Distance Classification.IEEETrans on Electrical Insulation,1993,28(6):1018-1024.
  • 3SATISH L,ZAENGL W S.Can Fractal Features be Used for Recognition 3-D Partial Discharge Patterns9 IEEE Trans on Dielectrics and Electrical Insulation,1995,2(3):352-359.
  • 4HOOF M,FREISLEBEN B,PATSCH R.PD Source Identification with Novel Discharge Parameters Using Counterpropagation Neural Networks.IEEE Trans on Dielectrics and Electrical Insulation,1997,4(1):17-32.
  • 5LALLFFLA E M,SATLSH L.Wavelet Analysis for Classification of Multi-source PD Patterns.IEEE Trans on Dielectrics and Electrical Insulation,2000,7(1):40-47.
  • 6MALLAT S.A Theory of Wavelet Multiresolution Signal Decomposition:The Wavelet Transform.IEEE Trans onPattern Analysis and Machine Intelligence,1989,11(7):673-693.
  • 7姜磊,朱德恒,李福祺,谈克雄,覃刚力,金显贺,王昌长,T.C.Cheng.基于人工神经网络的变压器绝缘模型放电模式识别的研究[J].中国电机工程学报,2001,21(1):21-24. 被引量:36
  • 8郑重,谈克雄,王猛,吴浩.基于脉冲波形时域特征的局部放电识别[J].电工电能新技术,2001,20(2):20-24. 被引量:37

共引文献29

同被引文献103

引证文献11

二级引证文献150

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部