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When internal faults occur in GIS equipment, such as spark discharge or corona discharge, it can cause SF6 gas to decompose and generate characteristic decomposition products such as SO2. The severity of discharge faults can be evaluated by measuring the concentration of SO2. However, current SO2 gas sensors on the market have limitations in terms of volume and sensitivity to specific gases, making it difficult to meet all needs. In response to this issue, this article has developed a dual channel SO2 detection system based on non dispersive infrared (NDIR) technology, which can accurately detect SO2 in SF6 gas environment and ensure that the detection results are not affected by other interfering gases. In addition, by simulating the decomposition of SF6 gas under different intensity spark discharge conditions, this article collected SO2 decomposition products of different concentrations. The comparative test results using gas chromatography show that the designed SO2 detection device has very high detection accuracy, with a maximum error of only ±7 ppm. This result validates the significant potential and advantages of the detection device in online monitoring of discharge faults in GIS equipment.

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High-Precision SO2 Detection in GIS Equipment Based on NDIR Sensor

  • 会议论文

  • 发表日期：

    2025年

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  • Liang Liu,
  • Peng Luo,
  • Zhi Yin,
  • Tingting Su,
  • Chensong Liu,
  • Yukun Chen,
  • Xiao Liu,
  • Jifeng Chu,
  • Aijun Yang

摘要

When internal faults occur in GIS equipment, such as spark discharge or corona discharge, it can cause SF6 gas to decompose and generate characteristic decomposition products such as SO2. The severity of discharge faults can be evaluated by measuring the concentration of SO2. However, current SO2 gas sensors on the market have limitations in terms of volume and sensitivity to specific gases, making it difficult to meet all needs. In response to this issue, this article has developed a dual channel SO2 detection system based on non dispersive infrared (NDIR) technology, which can accurately detect SO2 in SF6 gas environment and ensure that the detection results are not affected by other interfering gases. In addition, by simulating the decomposition of SF6 gas under different intensity spark discharge conditions, this article collected SO2 decomposition products of different concentrations. The comparative test results using gas chromatography show that the designed SO2 detection device has very high detection accuracy, with a maximum error of only ±7 ppm. This result validates the significant potential and advantages of the detection device in online monitoring of discharge faults in GIS equipment.