Advanced rotor fault diagnosis for medium-voltage induction motors via continuous transforms

  • Jose A. Antonino-Daviu*
  • , Joan Pons-Llinares
  • , Sang Bin Lee
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A number of field case studies for rotor fault diagnosis on medium-voltage induction motors operating in a petrochemical plant are presented in this paper. The methodology employed is based on analyzing the induction motor startup current with advanced signal processing tools (continuous transforms) that enable a capture of a 'complete picture' of the rotor condition. Indeed, unlike the classical tools that often rely on the detection of few fault frequencies, these new tools allow extraction of the evolution of a wide range of fault components during the startup transient and steady-state evolutions, which enables improved reliability. This is crucial in medium-high-voltage motors, where a false diagnosis may result in significant expense due to inspection, repair, or forced outage. An additional contribution of the study is its immunity to external voltage supply disturbances, which introduce components that are not related to the failure and which are difficult to detect with classical tools. The results of this study prove how the advanced continuous tools enable an improved visualization of the fault components, distinguishing them from the other components that are not linked to the failure.

    Original languageEnglish
    Article number7496874
    Pages (from-to)4503-4509
    Number of pages7
    JournalIEEE Transactions on Industry Applications
    Volume52
    Issue number5
    DOIs
    Publication statusPublished - 2016 Sept 1

    Bibliographical note

    Publisher Copyright:
    © 1972-2012 IEEE.

    Keywords

    • Fault diagnosis
    • induction motors
    • spectral analysis
    • transient analysis
    • wavelet transforms

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Industrial and Manufacturing Engineering
    • Electrical and Electronic Engineering

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