LIU Ge,ZHANG Meng-wei,QIN Fang,CHEN Bin,CHEN Jun-sen,YANG Hao-zhang.Detection of Water Content in Transformer Oil Based on Infrared Spectroscopy[J].Journal of Instrumental Analysis,2025,44(05):919-924.
LIU Ge,ZHANG Meng-wei,QIN Fang,CHEN Bin,CHEN Jun-sen,YANG Hao-zhang.Detection of Water Content in Transformer Oil Based on Infrared Spectroscopy[J].Journal of Instrumental Analysis,2025,44(05):919-924. DOI: 10.12452/j.fxcsxb.240915402.
Detection of Water Content in Transformer Oil Based on Infrared Spectroscopy
水分含量的大小直接影响变压器油的电气性能和变压器安全,对变压器油含水量的检测是变压器安全运行的重要保障。该文通过制备不同水分梯度油样,并进行红外光谱检测,建立了变压器油中含水量、吸光度、吸收峰面积的多元线性回归数学模型,并利用验证样对数学模型进行检验,提出了一种红外光谱法检测含水量的精确定量方法。结果表明含水变压器油红外光谱的吸收峰是水分子中羟基(—OH)吸收红外光能量产生振动所致,存在于变压器油中的水分子与水分子以及变压器油中某些添加剂之间发生氢键效应,使得电子云密度平均化,导致3 600~3 200 cm
The moisture content in transformer oil directly affects its electrical performance and may lead to safety hazards. Therefore,detecting moisture content is critical for ensuring the safe operation of transformers. By preparing oil samples with controlled moisture gradients and analyzing their infrared spectra,a multiple linear regression model correlating moisture content(
W
),absorbance at 3 400 cm
-1
(
A
),and absorption peak area(
S
) within 3 600-3 200 cm
-1
was established. The model was validated using independent samples,proposing an accurate quantitative method for moisture detection via infrared spectroscopy. The results indicated that the absorption peaks in water-containing transformer oil arise from hydroxyl(—OH) vibrations in water molecules. Hydrogen bonding between water molecules and additives in the oil reduced the electron cloud density,leading to a redshift(lower wavenumbers) and broadening of the absorption peaks in the 3 600-3 200 cm
-1
region. A quantitative model linking moisture content(
W
),absorbance at 3 400 cm
-1
(
A
),and absorption peak area(
S
) was established with high significance(
R
²=0.943,sig=0.003,
p
<
0.05) and accuracy(RMSE=0.005 12). The experimental data points uniformly distributed on the regression plane confirm the model’s robustness in calculating moisture content. This method improves the accuracy of moisture quantification in transformer oil and provides a theoretical basis for future online monitoring systems.
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references
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