Identificación de defectos en cables de media tensión aplicando métodos multivariables

Abstract

Partial discharges in high-voltage power cables

are a focus of concern due to their harmful

effects regarding insulation degradation.

Therefore, their fast and accurate identification

is of paramount importance. This paper deals

with the diagnosis and identification of cable

defects in medium-voltage XLPE insulated

cables. Partial discharge pulses are acquired

by means of a standard partial discharge

detector. Data acquired are further processed

by means of the fast Fourier transform and

by applying suitable multivariate feature

extraction and classification methods, namely

principal component analysis, canonical variate

analysis and k nearest neighbors. Experimental

results show that the proposed identification

methodology provides improved classification

accuracy, simplicity and very low time response

to classify a new sample object. Therefore, the

data processing system presented here is the

main contribution of this work, which can be

extended to other insulated cable types.