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 …

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 …

Reliability of power system is very essential for every nation to generate and transmit power
without interruption. Power transformer is one of the most significant electrical apparatus and …

To increase the classification accuracy of a protection scheme for power transformer, an
effective convolution neural network (CNN) extreme gradient boosting (XGBoost) …

This paper proposes a new approach based on combined Wavelet Transform-Extreme
Learning Machine (WT-ELM) technique for fault section identification (whether the fault is …

The dissolved gas-in-oil analysis is a prevailing methodology being extensively utilized to
diagnose incipient faults in oil-immersed power transformers. However distinct approaches …

This paper presents differential protection and condition monitoring scheme for power
transformer using ANN. This ANN-based scheme monitors different operating conditions of …

To improve the fault diagnosis accuracy for power transformers, this paper presents a kernel
based extreme learning machine (KELM) with particle swarm optimization (PSO). The …

The classification of distinct problems of insulators in the distribution networks is a task that
requires operator's experience. The applications of techniques to automate the inspection of …

This paper presents a new classification scheme for power transformer which effectively
discriminates between internal faults (phase to ground, phase to phase & phase to phase to …