A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

Álvarez Gómez, Fernando and Ortego la Moneda, Javier and Garnacho Vecino, Fernando and Sanchez-Uran Gonzalez, Miguel Angel (2016). A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters. "IEEE Transactions on Dielectrics and Electrical Insulation", v. 23 (n. 1); pp. 469-481. ISSN 1070-9878. https://doi.org/10.1109/TDEI.2015.005037.

Description

Title: A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters
Author/s:
  • Álvarez Gómez, Fernando
  • Ortego la Moneda, Javier
  • Garnacho Vecino, Fernando
  • Sanchez-Uran Gonzalez, Miguel Angel
Item Type: Article
Título de Revista/Publicación: IEEE Transactions on Dielectrics and Electrical Insulation
Date: February 2016
ISSN: 1070-9878
Volume: 23
Subjects:
Freetext Keywords: Partial discharges; Insulation testing; Interference suppression; Feature extraction; Pattern classification; Pattern recognition
Faculty: E.T.S.I. Diseño Industrial (UPM)
Department: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (16MB) | Preview

Abstract

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).

More information

Item ID: 41411
DC Identifier: http://oa.upm.es/41411/
OAI Identifier: oai:oa.upm.es:41411
DOI: 10.1109/TDEI.2015.005037
Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=7422593
Deposited by: Memoria Investigacion
Deposited on: 17 Jun 2016 08:09
Last Modified: 12 Mar 2019 08:08
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM