Artificial neural network based method for temperature correction in FDS measurement of transformer insulation
Author:
Publisher
IOP Publishing
Subject
Surfaces, Coatings and Films,Acoustics and Ultrasonics,Condensed Matter Physics,Electronic, Optical and Magnetic Materials
Link
https://iopscience.iop.org/article/10.1088/1361-6463/ab62c2/pdf
Reference29 articles.
1. Insulation condition diagnosis of oil-immersed paper insulation based on non-linear frequency-domain dielectric response
2. Effect of oil–paper–pressboard mass ratio on furfural content in transformer oil
3. Effect of moisture content on the production and partitioning of furfural in oil-paper insulation
4. Dissolved Gases Forecasting Based on Wavelet Least Squares Support Vector Regression and Imperialist Competition Algorithm for Assessing Incipient Faults of Transformer Polymer Insulation
5. Prediction of moisture present in cellulosic part of power transformer insulation using transfer function of modified debye model
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1. Evaluating the insulation condition of oil‐impregnated paper bushings based on the time constant database;IET Electric Power Applications;2024-07-07
2. Analysis of Temperature Dependences of the Loss Factor of Transformer by Method FDS;2024 9th International Youth Conference on Energy (IYCE);2024-07-02
3. Analysis of the Effect of Different Damped Forms on the High Voltage Frequency Domain Spectroscopy Characteristics of Oil-Paper Insulation;Lecture Notes in Electrical Engineering;2024
4. Assessing the moisture content of oil‐impregnated paper bushings with a simple and fast method;IET Electric Power Applications;2023-12-22
5. Correction of temperature effects in dielectric response tests in power transformers using artificial intelligence;2023-11-11
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