Data-driven estimation of multiple fault parameters in permanent magnet synchronous motors

Subhadeep Chakraborty, Chinmay Rao, Eric Keller, Asok Ray, Murat Yasar

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

    1 Scopus citations

    Abstract

    This paper presents symbolic analysis of time series data for estimation of multiple faults in permanent magnet synchronous motors (PMSM). The analysis is based on an experimentally validated dynamic model, where the flux linkage of the permanent magnet and friction in the motor bearings are varied in the simulation model to represent different stages of degradation. The fault magnitudes are estimated from the time series of the instantaneous line current. The behavior patterns of the PMSM are compactly generated as quasi-stationary state probability histograms associated with the finite state automata of its symbolic dynamic representation. The proposed fault estimation method is suitable for real-time execution on a limited-memory platforms, such as those used in sensor network nodes.

    Original languageEnglish (US)
    Title of host publication2009 American Control Conference, ACC 2009
    Pages204-209
    Number of pages6
    DOIs
    StatePublished - Nov 23 2009
    Event2009 American Control Conference, ACC 2009 - St. Louis, MO, United States
    Duration: Jun 10 2009Jun 12 2009

    Other

    Other2009 American Control Conference, ACC 2009
    Country/TerritoryUnited States
    CitySt. Louis, MO
    Period6/10/096/12/09

    All Science Journal Classification (ASJC) codes

    • Electrical and Electronic Engineering

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