Abstract：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.
宋睿敏, 王建新, 陈伟根, 王子懿, 张鑫源. 矿物油中糠醛液芯光纤增强拉曼光谱原位检测方法[J]. 电工技术学报, 2023, 38(24): 6828-6838.
Song Ruimin, Wang Jianxin, Chen Weigen, Wang Ziyi, Zhang Xinyuan. Detection Method for Furfural Dissolved in Mineral Oil Based on Liquid-Core Fiber Enhanced Raman Spectroscopy. Transactions of China Electrotechnical Society, 2023, 38(24): 6828-6838.
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