Absolute Value Principal Components Analysis (AVPCA) and Parameter Estimation (PE) to bearing fault detection using rotor speed signal monitoring — A comparative study

Moussa Hamadache, Dongik Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, a comparative experimental study between the Parameter Estimation (PE) technique and the Absolute Value Principal Component Analysis (AVPCA) algorithm to bearing fault detection using rotor speed signal monitoring is represented. The PE technique relies on the residuals between the input/output (Voltage/Speed) signals of the real system and of the estimated model. AVPCA, in other hand base on the Sum Square Error (SSE) distance between the training-databases and the tested-databases from just only the output signal (Speed) and its minimum. The experimental results reveal that the AVPCA algorithm is more effective in detecting bearing faults than the PE technique using rotor speed signal monitoring.
Original languageEnglish
Title of host publication 2016 IEEE Region 10 Symposium (TENSYMP)
Place of PublicationBali, Indonesia
PublisherIEEE Xplore
Pages367-372
ISBN (Electronic)9781509009312
ISBN (Print)9781509009329
DOIs
Publication statusPublished - 9 May 2016
Event2016 IEEE Region 10 Symposium - Sanur, Indonesia
Duration: 9 May 201611 May 2016

Conference

Conference2016 IEEE Region 10 Symposium
Abbreviated titleTENSYMP
Country/TerritoryIndonesia
CitySanur
Period9/05/1611/05/16

Keywords

  • Bearing fault detection
  • Parameter estimation
  • Absolute value principal component analysis
  • Rotor speed signal monitoring

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