Bearing damage detection based on statistical discrimination of stator current

T. Lindh, Jero Ahola, Joni-Kristian Kamarainen, V. Kyrki, J. Partanen

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

    16 Citations (Scopus)

    Abstract

    In this study, a method is presented for discriminating stator current signals from two classes, motors in normal condition and ones with a bearing failure. The study has two main objectives, to verify the former results on the bearing fault detection based on the stator current, and to show the applicability of the proposed method for the diagnosis based on frequency content. The method is based on statistical analysis of Gabor filter responses. In the empirical part of this study where the method is applied to the real measurements, the results indicate that it is not possible to detect a bearing fault if the internal radial clearance of the bearing is not adequate.

    Original languageEnglish
    Title of host publicationIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2003 - Proceedings
    PublisherIEEE
    Pages177-181
    Number of pages5
    ISBN (Print)0780378385, 9780780378384
    DOIs
    Publication statusPublished - 2003
    MoE publication typeA4 Article in a conference publication
    EventIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives - Stone Mountain, United States
    Duration: 24 Aug 200326 Aug 2003
    Conference number: 4

    Conference

    ConferenceIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives
    Abbreviated titleSDEMPED
    CountryUnited States
    CityStone Mountain
    Period24/08/200326/08/2003

    Keywords

    • Bandwidth
    • Condition monitoring
    • Failure analysis
    • Fault detection
    • Fault diagnosis
    • Frequency estimation
    • Induction motors
    • Information technology
    • Large Hadron Collider
    • Stators

    Fingerprint Dive into the research topics of 'Bearing damage detection based on statistical discrimination of stator current'. Together they form a unique fingerprint.

    Cite this