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Memorias de investigación
Artículos en revistas:
A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters
Año:2015
Áreas de investigación
  • Ingenierías,
  • Ingeniería eléctrica
Datos
Descripción
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).
Internacional
Si
JCR del ISI
Si
Título de la revista
IEEE Transactions on Dielectrics and Electrical Insulation.
ISSN
1070-9878
Factor de impacto JCR
1,278
Información de impacto
Volumen
DOI
Número de revista
Desde la página
469
Hasta la página
481
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Fernando Alvarez Gomez (UPM)
  • Autor: Javier Ortego La Moneda (UPM)
  • Autor: Fernando Garnacho Vecino (UPM)
  • Autor: Miguel Angel Sanchez-Uran Gonzalez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Robots y máquinas inteligentes
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
  • Departamento: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
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