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Ester insulating liquids feature a fire point above 300℃ and are biodegradability. It is often used as a substitute for mineral oil in transformer retrofilling engineering. Nevertheless, the old oil is difficult to be completely removed, and the residual mineral oil will deteriorate the physicochemical and dielectric properties of mixed system. Detecting the mineral oil content in the mixture is an important method for performance evaluation, but the existing detection methods are difficult to simultaneously balance accuracy and efficiency. In this paper, the applicability, accuracy, and economy of six detection methods including thermal conductivity method, kinematic viscosity method, fire point method, Fourier transform infrared spectroscopy (FTIR) method, dielectric properties method, and iodine value method in the detection of mineral oil content in mixed insulating liquids of natural esters (FR3, RAPO) and synthetic esters (KI50EX, TFO 100) systems were systematically compared. By constructing linear regression models between detection parameters and mineral oil mass fractions, the prediction accuracy of each method was evaluated based on the coefficient of determination (R2). The results show that for natural ester-based mixed systems, the 60℃ kinematic viscosity prediction method has the highest priority, followed by the 40℃ thermal conductivity method, iodine value method, and FTIR method. For synthetic ester-based mixed systems, the 60℃ kinematic viscosity prediction method is the most cost-effective, with the thermal conductivity and FTIR method following closely behind. The iodine value method is inapplicable to synthetic ester systems due to the saturated chemical structure of synthetic esters. Fire point tests cannot provide a clear indication of the residual mineral oil content but can help quickly determine whether mixed insulating liquids meet the K-level flame-retardant requirements. Dielectric parameters are significantly affected by environmental factors such as moisture and are not suitable as quantitative detection indicators for mineral oil residues.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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