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

Alvarez Gomez, Fernando; Ortego la Moneda, Javier; Garnacho Vecino, Fernando y 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.

Descripción

Título: A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters
Autor/es:
  • Alvarez Gomez, Fernando
  • Ortego la Moneda, Javier
  • Garnacho Vecino, Fernando
  • Sanchez-Uran Gonzalez, Miguel Angel
Tipo de Documento: Artículo
Título de Revista/Publicación: IEEE Transactions on Dielectrics and Electrical Insulation
Fecha: Febrero 2016
Volumen: 23
Materias:
Palabras Clave Informales: Partial discharges; Insulation testing; Interference suppression; Feature extraction; Pattern classification; Pattern recognition
Escuela: E.T.S.I. Diseño Industrial (UPM)
Departamento: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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).

Más información

ID de Registro: 41411
Identificador DC: http://oa.upm.es/41411/
Identificador OAI: oai:oa.upm.es:41411
Identificador DOI: 10.1109/TDEI.2015.005037
URL Oficial: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=7422593
Depositado por: Memoria Investigacion
Depositado el: 17 Jun 2016 08:09
Ultima Modificación: 31 Ago 2016 22:30
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