Fiber-Enhanced Raman Spectroscopy for Simultaneous Detection of Fault Characteristic Gases Dissolved in Transformer Oil

• Main Authors: Wang, Jianxin, Chen, Weigen, Wang, Pinyi, Zhou, Feng, Xiang, Shiyezi, Peng, Qingjun
• Format: Conference Proceeding
• Language: English
• Subjects: characteristic gases dissolved in transformer oil; Filling; Gas lasers; Gases; hollow-core anti-resonant fiber; Oil insulation; Power lasers; Raman scattering; Raman spectroscopy; Sensors
• ISSN: 2474-3852
• DOI: 10.1109/ICHVE49031.2020.9280048

Dissolved gas-in-oil analysis (DGA) is one of the most effective method to realize power transformers' operation status diagnosis. Fiber-enhanced Raman spectroscopy has the unique advantage of using one single wavelength laser to simultaneously achieve highly selective and sensitive detection of mixture gases within a few seconds, making it the most promising technology in gas sensing field. This paper developed an innovative Raman gas sensing system that used a 2-meter hollow-core anti-resonant fiber (HC-ARF), which confined most of the light in the hollow core and simultaneously worked as a sample container, to increase the effective interaction path length of light-analyte as well as the collection efficiency of Raman-scattered light. The Raman spectrum of mixed seven kinds of fault characteristic gases dissolved in transformer oil, including H 2 , CO, CO 2 , CH 4 , C 2 H 6 , C 2 H 4 , C 2 H 2 , was obtained and a limit of detection of 62, 194, 189, 34, 63, 128, 36 ppm for the characteristic Raman shift at 4156, 2143, 1388, 2917, 2955, 1625, 1972 cm −1 was achieved, respectively. The gas filling time for this novel HC-ARF was investigated by monitoring the Raman peak height of CH 4 at 2917 cm −1 until it tended to be unchanged. Moreover, the Raman peak intensity and width of CH 4 (2917 cm −1 ) at different laser power were studied. The results indicated that the Raman peak area and height showed a good linear relationship with the laser power, while the full width at half maximum (FWHM) was independent. On the basis of the superiority and versatility, we expect that FERS has high application-potential in transformers' fault diagnosis.