Data mining is a technological and scientific field that, over the years, has been gaining
more importance in many areas, attracting scientists, developers, and researchers around …

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 for the classification of the power system disturbances
using support vector machines (SVMs). The proposed approach is carried out at three serial …

This paper documents the condition-based maintenance (CBM) of power transformers, the
analysis of which relies on two basic data groups: structured (eg, numeric and categorical) …

The paper presents a method using deep learning framework based on convolution neural
network (CNN), for identification and localization of faults of transformer winding under …

In this paper, a new method for detecting the presence of broken rotor bars is presented. The
proposed approach is valid for induction machines started at constant frequency and …

The classical regression and Bayesian classification statistical techniques stand upon a
strict assumption that the underlying probability distribution is known. However, in real life …

This paper presents a support vector machine (SVM)-based method for preventive transient
stability control (TSC) of power systems. The features of the SVM model used in TSC are the …

Reliable detection of induction motor stator winding insulation failure at its early stages is a
challenging issue in modern industry. Insulation failure between small number of turns …

Fault diagnosis of power transformers is crucial to the healthy operation of transformers. In
order to enhance its accuracy and reliability, a new fault diagnosis method based on Set …