Fault detection and diagnosis in power transformers: a comprehensive review and classification of publications and methods
AR Abbasi - Electric Power Systems Research, 2022 - Elsevier
A challenging problem in the protection of power transformers is the fault detection and
diagnosis (FDD). FDD has an essential role in the reliability and safety of modern power …
diagnosis (FDD). FDD has an essential role in the reliability and safety of modern power …
Classification and discrimination among winding mechanical defects, internal and external electrical faults, and inrush current of transformer
In this paper, the mechanical faults of transformers including the winding radial deformation
and axial displacement on 1.6 MVA transformer winding are investigated. Then, by …
and axial displacement on 1.6 MVA transformer winding are investigated. Then, by …
Power transformer differential protection using current and voltage ratios
The main challenge in transformer protection is to find a fast and efficient differential relay
algorithm that isolates the transformer from the system causing least damage. Algorithm …
algorithm that isolates the transformer from the system causing least damage. Algorithm …
Thermo-hydraulic performance prediction of a solar air heater with circular perforated absorber plate using Artificial Neural Network
Abstract In this study, Multi-Layer Perceptron (MLP) model of the Artificial Neural Network
(ANN) is used to predict the thermo-hydraulic performance of a circular perforated absorber …
(ANN) is used to predict the thermo-hydraulic performance of a circular perforated absorber …
Efficient CNN‐XGBoost technique for classification of power transformer internal faults against various abnormal conditions
To increase the classification accuracy of a protection scheme for power transformer, an
effective convolution neural network (CNN) extreme gradient boosting (XGBoost) …
effective convolution neural network (CNN) extreme gradient boosting (XGBoost) …
Steady flow properties and spectral absorption potential of supercritical carbon dioxide nanofluids: experimental comparison and machine learning optimization
Z Su, L Yang, N Zhao, J Song, X Li, X Wu - Powder Technology, 2024 - Elsevier
To improve the performance of the power cycle and accelerate the realization of the carbon
neutrality goal, the development and application of nanofluids are imminent. In this research …
neutrality goal, the development and application of nanofluids are imminent. In this research …
Identification of internal fault against external abnormalities in power transformer using hierarchical ensemble extreme learning machine technique
Various unwanted phenomena that are taken place in the transformer may occasionally mal‐
operate selected fault classification based protective schemes. Hence, it is necessary to …
operate selected fault classification based protective schemes. Hence, it is necessary to …
Time–Frequency Decomposition Based Protection Scheme for Power Transformer—Simulation and Experimental Validation
A new protection scheme for power transformers using time–frequency decomposition is
presented. On detecting an abnormal condition based on the average energy of both sides …
presented. On detecting an abnormal condition based on the average energy of both sides …
A denoising-classification neural network for power transformer protection
Z Li, Z Jiao, A He, N Xu - … and Control of Modern Power Systems, 2022 - ieeexplore.ieee.org
Artificial intelligence (AI) can potentially improve the reliability of transformer protection by
fusing multiple features. However, owing to the data scarcity of inrush current and internal …
fusing multiple features. However, owing to the data scarcity of inrush current and internal …
Design and development of fault classification algorithm based on relevance vector machine for power transformer
Identification of faults within power transformers is the means of ensuring unit transformer
protection. Existing relay maloperates during abnormalities such as magnetising inrush, CT …
protection. Existing relay maloperates during abnormalities such as magnetising inrush, CT …