Abstract Dissolved Gas Analysis (DGA) is a standout diagnostic strategy to recognise
incipient faults and monitor the condition of oil-immersed transformers. It correlates the …

Power transformers are an indispensable equipment in power transmission and distribution
systems, and failures or hidden defects in power transformers can cause operational and …

Transformers are vital components of power systems as they are situated between energy
generation and consumers and their failure disrupts the use of electrical energy. Therefore …

Support vector machine (SVM) is a novel machine learning method based on statistical
learning theory (SLT). SVM is powerful for the problem with small sampling, nonlinear and …

Transformers are one of the most important and complex components of electricity
transmission and distribution. To have a reliable electricity supply, it is necessary to give …

This paper presents an integrated model based upon the fuzzy approach and evidential
reasoning decision-making approach to condition assessment of power transformers. An …

This paper presents a new approach to incipient fault diagnosis in power transformers,
based on the results of dissolved gas analysis. A set of autoassociative neural networks or …

Dissolved gas analysis is an effective method for the early detection of incipient fault in
power transformers. To improve the capability of interpreting the result of dissolved gas …

This paper describes the development and implementation of a tool for the diagnosis of
faults in power transformers through the analysis of dissolved gases in oil. The …

Methane is one of the indicative gases in power transformer oil, and the detection of
methane dissolved in oil with high accuracy is of great importance for dissolved gases …