Detection Method for Furfural Dissolved in Mineral Oil Based on Liquid-Core Fiber Enhanced Raman Spectroscopy

被引：0
|
作者：
Song R. [1 ]
Wang J. [1 ]
Chen W. [1 ]
Wang Z. [1 ]
Zhang X. [1 ]
机构：
[1] State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2023年 / 38卷 / 24期
关键词：
furfural in oil; liquid-core fiber enhancement; Oil-immersed power equipment; Raman spectroscopy;
D O I：
10.19595/j.cnki.1000-6753.tces.221789
中图分类号：
学科分类号：
摘要：
Oil-immersed power equipment is one of the core equipment in the power system. It undertakes the tasks of voltage level conversion, energy transmission, power distribution, and line support in the power grid. Its insulation status is crucial. The paper insulation of oil-immersed power equipment is mainly composed of cellulose. Affected by electricity and heat, the cellulose in paper insulation undergoes decomposition, resulting in the reduction of polymerization and mechanical strength of paper insulation. The process is accompanied by the dissolution of the cracking products in the insulating oil, such as furfural, methanol, acetone, ethyl acetate, etc. Furfural content in the mineral oil can effectively represent the insulation aging status of oil-immersed power equipment. Furfural, as an important aging characteristic, can effectively reflect the degree of polymerization of insulation paper. Therefore, accurately detecting furfural content in the oil is critical for the safe and dependable operation of oil-immersed power equipment, even the power grid. Compared with traditional methods, Raman spectroscopy is a non-invasive detection method without sample pre-processing. It is reliable and straightforward. However, it is challenging to meet the demand for detecting dissolved furfural in oil of oil-immersed power equipment precisely due to its weak signal intensity. Liquid-core fiber can enhance spatial transmission efficiency and improve the collection efficiency of Raman scattering due to its optical properties. In this paper, the research on the in-situ detection method of furfural in oil based on liquid-core fiber-enhanced Raman spectroscopy is carried out; An adapter to simultaneously realize position fixing, laser coupling, and liquid feeding of liquid-core fibers has been developed; An experimental platform for liquid-core fiber-enhanced Raman spectroscopy was set up. The transmission characteristics of the liquid-core fiber for insulating oil were obtained, and the suitable fiber length for insulating oil detection was determined to be 50 cm. In this paper, the vibration model of the furfural molecule was simulated and calculated based on DFT density functional theory using Gaussian simulation software, and its vibration attribution was determined. A model of multi-molecular furfural and its composite model with Icosane was established to research its vibration characteristics in insulating oil further, and it provides a theoretical basis for experimental analysis. Insulating oils containing different concentrations of furfural were measured. The mathematical model of the furfural concentration in oil and its internal standardized Raman peak intensity was established, and the accurate quantitative detection of furfural in oil was realized. The limit of detection concentration reached 0.164 mg/L, corresponding to the range of 656~751 that the degree of polymerization of insulation paper. In this paper, a linear model, and a model modified by the internal standard method were used to perform ten independent backtesting on samples with known concentrations. The internal standard modified model is more stable than the linear one, with a maximum offset of −1.32%. Insulating oil samples containing furfural were also tested for stability experiments, and the coefficient of variation of the characteristic peak intensity of furfural in 120 sets of data was 0.68%. The research results show that the detection method of furfural in oil based on liquid-core fiber-enhanced Raman spectroscopy (LC-FERS) features simple, good stability, high sensitivity, and fast. It provides a new method for rapid and accurate detection of furfural in the oil of oil-immersed power equipment. © 2023 Chinese Machine Press. All rights reserved.
引用
收藏
页码：6817 / 6827
页数：10
相关论文
共 39 条
  • [1] Li Yuan, Liu Ning, Liang Yu, Et al., A model of load capacity assessment for oil-immersed transformer by using temperature rise characteristics, Proceedings of the CSEE, 38, 22, pp. 6737-6746, (2018)
  • [2] Chen Tunan, Ma Fengxiang, Wang Liufang, Et al., Application of polymers membrane in dissolved gas analysis: a review, Transactions of China Electrotechnical Society, 37, 3, pp. 750-766, (2022)
  • [3] Deng Yongqing, Ruan Jiangjun, Dong Xuzhu, Et al., Establishment and verification of 10kV oil immersed transformer winding hot spot temperature inversion model based on streamline analysis, Proceedings of the CSEE, 43, 8, pp. 3191-3204, (2023)
  • [4] Chen Weigen, Teng Li, Liu Jun, Et al., Transformer winding hot-spot temperature prediction model of support vector machine optimized by genetic algorithm, Transactions of China Electrotechnical Society, 29, 1, pp. 44-51, (2014)
  • [5] Dong Ming, Wang Li, Wu Xuezhou, Et al., Status and progress in study of dielectric response technology for oil-paper insulation, High Voltage Engineering, 42, 4, pp. 1179-1189, (2016)
  • [6] Wang Jianxin, Chen Weigen, Wang Pinyi, Et al., Analysis of fault characteristic gases dissolved in transformer oil based on hollow-core anti-resonant fiber-enhanced Raman spectroscopy, Proceedings of the CSEE, 42, 16, pp. 6136-6144, (2022)
  • [7] Yu Yongjin, Jiang Yanan, Li Changyun, Prediction method of insulation paper remaining life with mechanical-thermal synergy based on whale optimization algorithm-long-short term memory model, Transactions of China Electrotechnical Society, 37, 12, pp. 3162-3171, (2022)
  • [8] Chen Weigen, Zhang Zhixian, Li Jian, Et al., Intelligent sensing technology for power equipment state parameters, Proceedings of the CSEE, 40, S1, pp. 323-342, (2020)
  • [9] Jiang Yanan, Yu Yongjin, Li Changyun, Evaluation method of insulation paper deterioration status with mechanical-thermal synergy based on improved TOPSIS model, Transactions of China Electrotechnical Society, 37, 6, pp. 1572-1582, (2022)
  • [10] Zhao Lihua, Xu Li, Liu Yan, Et al., Transformer mechanical fault diagnosis method based on symmetrized dot patter and image matching, Transactions of China Electrotechnical Society, 36, 17, pp. 3614-3626, (2021)
1234