A Novel Method of Fault Prediction in Transformer Oil using Infrared Spectroscopy

Anurag Dutta, S. Karmakar, Hussain Kalathiripi
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Abstract

Dissolved gas analysis (DGA) is the most widely used technique for predicting incipient faults in transformer oil. In order to perform DGA, the concentration of dissolved gases such as Methane (CH4), Ethylene (C2H4) and Acetylene (C2H2) are required. The concentration of these gases can be determined by means of Gas Chromatography (GC) which is the most globally used technique. However, this technique requires an experienced operator, has high maintenance and running costs, and time consuming as well. In view of these issues, a new method of fault prediction is proposed in this paper that makes use of the absorption phenomena of transformer oil. Fourier Transform Infrared (FTIR) Spectroscopy was performed on oil samples that have been degraded due to the accumulative and repetitive impact of high voltage impulses. The FTIR spectra gave the peak absorbance values of the dissolved gases viz; CH4, C2H4 and C2H2. Finally, the Duval triangle method was implemented for fault prediction. Also, other properties of oil such as breakdown voltage and dielectric constant have also been evaluated.
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基于红外光谱的变压器油故障预测新方法
溶解气体分析(DGA)是变压器油早期故障预测中应用最广泛的技术。为了进行DGA,需要甲烷(CH4)、乙烯(C2H4)和乙炔(C2H2)等溶解气体的浓度。这些气体的浓度可以通过气相色谱法(GC)来测定,这是全球使用最广泛的技术。然而,该技术需要经验丰富的操作人员,维护和运行成本高,而且耗时长。针对这些问题,本文提出了一种利用变压器油的吸收现象进行故障预测的新方法。傅里叶变换红外光谱(FTIR)对由于高压脉冲的累积和重复影响而降解的油样进行了分析。FTIR光谱给出了溶解气体的峰值吸光度值为;CH4, C2H4和C2H2。最后,采用Duval三角法进行故障预测。此外,还对油的其他特性如击穿电压和介电常数进行了评价。
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