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Optimum Optical Length of the Gas Cell Used for Monitoring Gas-In-Oil with FTIR 被引量:1

Optimum Optical Length of the Gas Cell Used for Monitoring Gas-In-Oil with FTIR
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摘要 Dedicated experiments are designed to collect the infrared spectra of dissolved gas-in-oil of power transformers. Spectra of diagnostic gases are collected by 3 different laboratorial FTIR spectrometers using 3 different gas cells with various sets of equipment parameters. A formula is deduced to calculate the shortest optical length to detect a specific concentration according to measurements on gases with known concentrations near to the minimum detection limit. Collected spectra and calculated results suggested that the optimum optical length of the gas cell should be 150 mm to realize on-line monitoring of diagnostic gases within the required concentration range. At the end, an economic novel design of the gas cell is proposed based on the optimum length. Dedicated experiments are designed to collect the infrared spectra of dissolved gas-in-oil of power transformers. Spectra of diagnostic gases are collected by 3 different laboratorial FTIR spectrometers using 3 different gas cells with various sets of equipment parameters. A formula is deduced to calculate the shortest optical length to detect a specific concentration according to measurements on gases with known concentrations near to the minimum detection limit. Collected spectra and calculated results suggested that the optimum optical length of the gas cell should be 150 mm to realize on-line monitoring of diagnostic gases within the required concentration range. At the end, an economic novel design of the gas cell is proposed based on the optimum length.
出处 《Journal of Beijing Institute of Technology》 EI CAS 2003年第1期59-63,共5页 北京理工大学学报(英文版)
关键词 FTIR gas cell power transformer DGA optical length dissolved gas-in-oil FTIR gas cell power transformer DGA optical length dissolved gas-in-oil
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  • 1李红雷,周方洁,谈克雄,高文胜.用于变压器在线监测的傅里叶红外定量分析[J].电力系统自动化,2005,29(18):62-65. 被引量:29
  • 2徐文,王大忠,周泽存,陈珩.人工神经网络在变压器特征气体法故障诊断中的应用[J].高电压技术,1996,22(2):27-30. 被引量:26
  • 3周利军,吴广宁,宿冲,王洪亮.变压器油中故障气体的复合预测方法[J].西南交通大学学报,2006,41(2):150-153. 被引量:20
  • 4DUVAL M. A review of faults detectable by gas-in-oil analysis in transformers[ J ]. IEEE Electrical Insulation Magazine,2002,18 (3) : 8- 17.
  • 5DUVAL M. New techniques for dissolved gas- in- oil analysis [ J ]. IEEE Electrical Insulation Magazine, 2003,19 (2) :6-15.
  • 6GUARDADO J L,NAREDO J L,MORENO P,et al. A comparative study of neural network efficiency in power transformers diagnosis using dissolved gas analysis [J]. IEEE Trans Power Delivery ,2001,16(4) :643-647.
  • 7MIN Sang-won,SOHN Jin-man,PARK Jong-keun. Adaptive fault section estimation using matrix representation with fuzzy relations [ J ]. IEEE Trans Power System, 2004,19 (2) : 842- 848.
  • 8FORT A,GREGORKIEWITZ M,MACHETTI N,et al. Versatile headspace and electronics for measurements with gas sensor arrays[C]//Proceedings of the 17 th IEEE Instrumentation and Measurement Technology Conference(IMTC). Bahimore,USA:IEEE, 2000:1458-1462.
  • 9ARAKELIAN V G. The long way to the automatic chromatographic analysis of gases dissolved in insulating oil[J]. IEEE Electrical Insulation Magazine, 2004,20 (6) : 8 - 25.
  • 10贾瑞君.关于变压器油中溶解气体在线监测的综述[J].电网技术,1998,22(5):49-55. 被引量:25

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