Compared with conventional methods of fault diagnosis for power transformers, which have
defects such as imperfect encoding and too absolute encoding boundaries, this paper …

Prognostics and health management (PHM) has emerged as an intelligent solution to
improve the availability of manufacturing systems. PHM consists of system health …

In this work, Dissolved gas Analysis (DGA) has been implemented using soft computing
models namely fuzzy logic and Adaptive Neuro fuzzy inference system (ANFIS). DGA has …

This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in
unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation …

Power transformer is an essential component for the stable and reliable operation of
electrical power grid. The traditional transformer fault diagnostic methods based on …

E-Nose finds its use in a wide range of applications such as quality assessment in food
processing to toxic gas identification in chemical industry either in the offline or online mode …

In this paper, a transformer incipient fault diagnosis model has been developed with the help
of an artificial neural network (ANN), taking into account the difference in the energy …

Accurate faults diagnosis in power transformers is important for utilities to schedule
maintenance and minimises the operation cost. Dissolved gas analysis (DGA) is one of the …

The article presents results of oil-dissolved gas analysis for 239 units of high-voltage
equipment with faults under which acetylene is the key gas. The analysis revealed 13 types …

The article describes a method for detecting developing defects in high-power oil-filled
transformers, based on the results of analysis of dissolved gases in oil. It has been found …