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Transformer Winding Condition Assessment Using Feedforward Artificial Neural Network and Frequency Response Measurements

, and . Energies, 14 (11): 3227 (2021)
DOI: 10.3390/en14113227

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A New Approach for High Frequency Modelling of Disc Windings, , , , and . (2018)Development and Optimization of Methods for Objective Interpretation of Frequency Response Analysis of Power Transformers., , and . (2018)Towards Objective Interpretation of Frequency Response of Power Transformers, and . (2019)A Comprehensive Analysis of Windings Electrical and Mechanical Faults Using a High-Frequency Model, and . Energies 2020, (December 2019)Transformer Winding Fault Classification and Condition Assessment Based on Random Forest Using FRA, and . Energies, 16 (9): 3714 (2023)Transformer Winding Condition Assessment Using Feedforward Artificial Neural Network and Frequency Response Measurements, and . Energies, 14 (11): 3227 (2021)FRA lookup charts for the quantitative determination of winding axial displacement fault in power transformers, and . IET electric power applications, 14 (12): 2370-2377 (2020)Analysis of Statistical Methods for Assessment of Power Transformer Frequency Response Measurements, , and . (2020)Sensitivity of Connection Schemes for Detection of Axial Displacement of Transformer Winding by Frequency Response Analysis, , and . 2018 IEEE International Conference on High Voltage Engineering and Application (ICHVE), IEEE, (2018)Optimization of FRA by an Improved Numerical Winding Model: Disk Space Variation, , and . (2018)