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Article

Prediction of Moisture and Aging Conditions of Oil-Immersed Cellulose Insulation Based on Fingerprints Database of Dielectric Modulus

Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, Guangxi, China
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Polymers 2020, 12(8), 1722; https://doi.org/10.3390/polym12081722
Received: 7 July 2020 / Revised: 26 July 2020 / Accepted: 27 July 2020 / Published: 31 July 2020
Frequency-domain spectroscopy (FDS) is demonstrated to be affected by electrode polarization and conductance behavior in the low-frequency ranges, which causes the unreliable prediction results of transformer cellulose insulation. In order to solve this issue, a fingerprint database based on the dielectric modulus is reported to predict the degree of polymerization (DP) and moisture content of cellulose insulation. In the current work, the relevant fingerprints that characterize the insulation conditions are obtained by studying the dielectric modulus curves of cellulose insulation with various insulation conditions, as well as the DC conductivity of transformer oil. Then, the dielectric modulus fingerprint database is established in the lab, and the accuracy of the reported fingerprint database is later verified. As a potential tool, the dielectric modulus fingerprint database is tested by several samples, and the results demonstrate that the accuracy of this method is more than 80%. In that respect, an interesting discovery of this paper is that the dielectric modulus fingerprint database may be a helpful tool for conditions prediction of the transformer cellulose insulation system. View Full-Text
Keywords: transformer; oil-immersed cellulose insulation; frequency-domain spectroscopy (FDS); aging condition; moisture evaluation transformer; oil-immersed cellulose insulation; frequency-domain spectroscopy (FDS); aging condition; moisture evaluation
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MDPI and ACS Style

Zhang, Y.; Li, S.; Fan, X.; Liu, J.; Li, J. Prediction of Moisture and Aging Conditions of Oil-Immersed Cellulose Insulation Based on Fingerprints Database of Dielectric Modulus. Polymers 2020, 12, 1722. https://doi.org/10.3390/polym12081722

AMA Style

Zhang Y, Li S, Fan X, Liu J, Li J. Prediction of Moisture and Aging Conditions of Oil-Immersed Cellulose Insulation Based on Fingerprints Database of Dielectric Modulus. Polymers. 2020; 12(8):1722. https://doi.org/10.3390/polym12081722

Chicago/Turabian Style

Zhang, Yiyi, Sheng Li, Xianhao Fan, Jiefeng Liu, and Jiaxi Li. 2020. "Prediction of Moisture and Aging Conditions of Oil-Immersed Cellulose Insulation Based on Fingerprints Database of Dielectric Modulus" Polymers 12, no. 8: 1722. https://doi.org/10.3390/polym12081722

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