Induction motor fault detection by using Wavelet decomposition on dq0 components

  • J. Cusido*
  • , J. A. Rosero
  • , J. A. Ortega
  • , A. Garcia
  • , L. Romeral
  • *Corresponding author for this work

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

27 Citations (Scopus)

Abstract

Early detection of interturn shorts during motor operation would eliminate consequential damage to adjacent coils and the stator core, then reducing repair costs and motor outage time. In addition to the benefits gained from early detection of turn insulation breakdown, significant advantages would accrue by locating the faulted coil within the stator winding. Fault location would not only increase the speed of the repair, but would also permit more optimal scheduling of the repair outage. Motor Current Signature Analysis (MCSA) method is widely used as a diagnose tool for industrial applications. On the other hand, Park's transform is the most popular transformation used in vector control algorithms. By analyzing the current spectra of dq0 Park components with MCSA method it is possible to improve earlier fault detection. Moreover, using Wavelet transform as signal analysis method it is possible to reduce signal noise effects. Experimental results clearly corroborate the main aim of the paper.

Original languageEnglish
Title of host publicationInternational Symposium on Industrial Electronics 2006, ISIE 2006
Pages2406-2411
Number of pages6
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventInternational Symposium on Industrial Electronics 2006, ISIE 2006 - Montreal, QC, Canada
Duration: 9 Jul 200613 Jul 2006

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume3

Conference

ConferenceInternational Symposium on Industrial Electronics 2006, ISIE 2006
Country/TerritoryCanada
CityMontreal, QC
Period9/07/0613/07/06

Keywords

  • Electrical drives
  • Fault detection
  • Induction motor
  • Inter turns shorts
  • Wavelet analysis
  • dq0 transform

Fingerprint

Dive into the research topics of 'Induction motor fault detection by using Wavelet decomposition on dq0 components'. Together they form a unique fingerprint.

Cite this