Radial basis function-based neural network for harmonics detection

Cheng I. Chen, Gary W. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

The widespread application of power electronic loads has led to increasing harmonic pollution in the supply system. In order to prevent harmonics from deteriorating the power quality, detecting harmonic components for harmonic mitigations becomes a critical issue. In this paper, an effective procedure based on the radial basis function neural network is proposed to detect harmonic amplitudes of the measured signal. By comparing with several commonly used methods, it is shown that the proposed solution procedure yields more accurate results and requires less sampled data for harmonics assessment.

Original languageEnglish
Title of host publicationProceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
Pages486-491
Number of pages6
DOIs
StatePublished - 2010
Event5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 - Taichung, Taiwan
Duration: 15 Jun 201017 Jun 2010

Publication series

NameProceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010

Conference

Conference5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
Country/TerritoryTaiwan
CityTaichung
Period15/06/1017/06/10

Keywords

  • Adaptive linear combiner
  • Back propagation neural network
  • Fast Fourier transform
  • Harmonics
  • Radial basis function neural network

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