SciELO - Scientific Electronic Library Online

 
vol.11 issue1The Euler-Poincaré Formula Through Contact Surfaces of Voxelized ObjectsOptimization of Turning Operations by Using a Hybrid Genetic Algorithm with Sequential Quadratic Programming author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Journal of applied research and technology

On-line version ISSN 2448-6736Print version ISSN 1665-6423

Abstract

MOGHIMI HAJI, M.; VAHIDI, B.  and  HOSSEINIAN, S. H.. Current Transformer Saturation Detection Using Gaussian Mixture Models. J. appl. res. technol [online]. 2013, vol.11, n.1, pp.79-87. ISSN 2448-6736.

This paper presents a novel current transformer (CT) saturation detection approach based on Gaussian Mixture Models (GMMs). High accuracy is the advantage of this method. GMMs are trained with secondary current of CT. The appropriate performance of the proposed method is tested by simulation of different fault conditions in PSCAD/EMTDC software. The results show that the trained GMMs can successfully detect CT saturation with high accuracy.

Keywords : CT saturation; GMM; protective relaying; transient analysis.

        · text in English     · English ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License