Classification of partial discharge in pin type insulators using fingerprints and neural networks

Research output: Contribution to conferencePaper

Abstract

The classification of partial discharge (PD) or partial breakdown (PB) is an important issue that helps to identify the cause of this electrical phenomenon in pin type insulators. In this work, a PD classification method based on neural networks (NN) is proposed. This sorting technique consists of three parts. First, the detection and measurement of partial discharge are achieved by using a digital finite impulse response (FIR) filter, whose main objective is to obtain electrical charges with significant characteristics of the PB. The second part of the process deals with the classification of partial discharge. A statistical analysis is implemented to obtain PD patterns or fingerprints which are classified by a neural network. Finally, the third part of the proposed method focuses on interpreting the information obtained from the NN and determining the PD current in the pin isolator. The results show that this proposed technique of analysis and detection of partial discharge in pin type isolators is successful in optimizing the time of analysis and classification of PB.

Original languageEnglish
Pages1-6
Number of pages6
DOIs
StatePublished - 16 Jan 2018
Event2017 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2017 - Ixtapa, Mexico
Duration: 8 Nov 201710 Nov 2017

Conference

Conference2017 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2017
Abbreviated titleROPEC 2017
CountryMexico
CityIxtapa
Period8/11/1710/11/17

Keywords

  • electrical charge
  • neural network
  • partial breakdown
  • Partial discharge
  • PD analysis
  • pin type insulators

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