A neural network based response model for high voltage circuit-breaker testing

Research output: Contribution to journalArticlepeer-review


Innovative test methods for circuit breakers are constantly sought after to reduce maintenance time and costs, yet still provide accurate assessment of this critical substation equipment. This paper proposes a novel method for response modelling of high voltage SF6 circuit breakers, based on artificial neural networks, to provide a means of assessing its condition. The proposed method enables a timing response model of the circuit breaker to be developed using trip command parameters. In this paper, an experimental setup is used to perform trip response testing of a three-phase 75 kV circuit breaker. The obtained data is then used to train, validate and test a Bayesian regularised artificial neural network that can predict response times of the breaker for a given set of trip command parameters.

Original languageEnglish
Pages (from-to)311-317
Number of pages7
JournalAdvances in Electrical and Electronic Engineering
Issue number3
Publication statusPublished - 2018


  • Circuit breaker
  • Condition assessment
  • Neural network
  • Response model

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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