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Fault diagnosis based on discrete wavelet transform and ART2 neural network

  • Kyungpook National University

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

3 Scopus citations

Abstract

In this paper we proposed a method of fault diagnosis for dynamic system based on DWT(discrete wavelet transform) and ART2 NN (adaptive resonance theory 2 neural network). In the proposed method, the fault is detected when the errors between the system output and the nominal system output cross a predetermined threshold. Once a fault in the system is detected, the ART2 NN fault classifier isolates the fault. The algorithm contains three main steps: a fault detection part by threshold test, a data preprocessing part via DWT and a fault isolation part by fault classifier. The simulation results demonstrate the effectiveness of the proposed fault diagnosis method based on DWT and ART2 NN.

Original languageEnglish
Title of host publicationProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
PublisherSociety of Instrument and Control Engineers (SICE)
Pages3365-3370
Number of pages6
ISBN (Print)9784907764364
StatePublished - 2010

Publication series

NameProceedings of the SICE Annual Conference

Keywords

  • ART2 neural network
  • Discrete wavelet transform
  • Fault detection
  • Fault isolation

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