Conventional methods of dissolved gas analysis using oil-immersed power transformer for fault diagnosis: A review

MS Ali, A Omar, ASA Jaafar, SH Mohamed - Electric Power Systems …, 2023 - Elsevier
This review paper summarizes the discoveries made about dissolved gas analysis (DGA)
conventional methods around the decade. DGA is a well-known diagnostic tool to classify …

State-of-the-art review on asset management methodologies for oil-immersed power transformers

L Jin, D Kim, A Abu-Siada - Electric Power Systems Research, 2023 - Elsevier
Owing to their vital function and high cost, oil-immersed power transformers represent key
links in electricity grids. While extensive effort has been invested by industry in developing …

[HTML][HTML] Improvement of power transformer fault diagnosis by using sequential Kalman filter sensor fusion

M Demirci, H Gözde, MC Taplamacioglu - International Journal of Electrical …, 2023 - Elsevier
Power transformers are one of the most important and costly equipment for the reliability and
continuity of electrical power systems. For this reason, continuous monitoring of power …

[HTML][HTML] Precise transformer fault diagnosis via random forest model enhanced by synthetic minority over-sampling technique

RA Prasojo, MAA Putra, ME Apriyani… - Electric Power Systems …, 2023 - Elsevier
Power transformers are considered one of the power system's most critical and expensive
assets. In this regard, it is vital to assess the fault within the power transformer considering …

Power transformer fault diagnosis based on a self-strengthening offline pre-training model

M Zhong, S Yi, J Fan, Y Zhang, G He, Y Cao… - … Applications of Artificial …, 2023 - Elsevier
Accurate transformer fault diagnosis is crucial for maintaining the power system stability.
Due the complex operation condition of the transformer, its faults are with the characteristic …

Designing efficient and sustainable predictions of water quality indexes at the regional scale using machine learning algorithms

A Derdour, A Jodar-Abellan, MÁ Pardo, SSM Ghoneim… - Water, 2022 - mdpi.com
Water quality and scarcity are key topics considered by the Sustainable Development Goals
(SDGs), institutions, policymakers and stakeholders to guarantee human safety, but also …

A real-time transformer discharge pattern recognition method based on CNN-LSTM driven by few-shot learning

Q Zheng, R Wang, X Tian, Z Yu, H Wang… - Electric Power Systems …, 2023 - Elsevier
The safe application of discharge equipment, such as transformers, is related to the
reliability of smart power grid and is crucial to the stable operation of the power system …

Improved intelligent methods for power transformer fault diagnosis based on tree ensemble learning and multiple feature vector analysis

A Hechifa, A Lakehal, A Nanfak, L Saidi, C Labiod… - Electrical …, 2024 - Springer
This paper discusses the impact of the feature input vector on the performance of dissolved
gas analysis-based intelligent power transformer fault diagnosis methods. For this purpose …

Spectral proper orthogonal decomposition and machine learning algorithms for bearing fault diagnosis

A Afia, F Gougam, W Touzout, C Rahmoune… - Journal of the Brazilian …, 2023 - Springer
Vibration analysis has been extensively exploited for bearing fault diagnosis. However,
signal acquisition is quite expensive since external hardware is required. Moreover, for …

Fault diagnosis of transformer using artificial intelligence: A review

Y Zhang, Y Tang, Y Liu, Z Liang - Frontiers in Energy Research, 2022 - frontiersin.org
Transformer is one of the important components of the power system, capable of transmitting
and distributing the electricity generated by renewable energy sources. Dissolved Gas …