Detection and estimation of demagnetization faults in permanent magnet synchronous motors

Subhadeep Chakraborty, Eric Keller, Asok Ray, Jeffrey Mayer

    Research output: Contribution to journalArticle

    28 Citations (Scopus)

    Abstract

    This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation of the PMSM. The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault. A special-purpose test bed has been designed and fabricated for experimental validation of the health monitoring algorithm via controlled accelerated deterioration of magnetization in the PMSM. The performance of the proposed algorithm has been compared with that of a classical motor current signature analysis (MCSA) procedure as well as with a benchmark particle filter for fault detection in PMSMs.

    Original languageEnglish (US)
    Pages (from-to)225-236
    Number of pages12
    JournalElectric Power Systems Research
    Volume96
    DOIs
    StatePublished - Jan 7 2013

    Fingerprint

    Demagnetization
    Synchronous motors
    Permanent magnets
    Dynamical systems
    Health
    Monitoring
    Fault detection
    Deterioration
    Magnetization
    Identification (control systems)

    All Science Journal Classification (ASJC) codes

    • Energy Engineering and Power Technology
    • Electrical and Electronic Engineering

    Cite this

    Chakraborty, Subhadeep ; Keller, Eric ; Ray, Asok ; Mayer, Jeffrey. / Detection and estimation of demagnetization faults in permanent magnet synchronous motors. In: Electric Power Systems Research. 2013 ; Vol. 96. pp. 225-236.
    @article{fd207f254ff34913ab1355e3e7983c30,
    title = "Detection and estimation of demagnetization faults in permanent magnet synchronous motors",
    abstract = "This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation of the PMSM. The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault. A special-purpose test bed has been designed and fabricated for experimental validation of the health monitoring algorithm via controlled accelerated deterioration of magnetization in the PMSM. The performance of the proposed algorithm has been compared with that of a classical motor current signature analysis (MCSA) procedure as well as with a benchmark particle filter for fault detection in PMSMs.",
    author = "Subhadeep Chakraborty and Eric Keller and Asok Ray and Jeffrey Mayer",
    year = "2013",
    month = "1",
    day = "7",
    doi = "10.1016/j.epsr.2012.11.005",
    language = "English (US)",
    volume = "96",
    pages = "225--236",
    journal = "Electric Power Systems Research",
    issn = "0378-7796",
    publisher = "Elsevier BV",

    }

    Detection and estimation of demagnetization faults in permanent magnet synchronous motors. / Chakraborty, Subhadeep; Keller, Eric; Ray, Asok; Mayer, Jeffrey.

    In: Electric Power Systems Research, Vol. 96, 07.01.2013, p. 225-236.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Detection and estimation of demagnetization faults in permanent magnet synchronous motors

    AU - Chakraborty, Subhadeep

    AU - Keller, Eric

    AU - Ray, Asok

    AU - Mayer, Jeffrey

    PY - 2013/1/7

    Y1 - 2013/1/7

    N2 - This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation of the PMSM. The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault. A special-purpose test bed has been designed and fabricated for experimental validation of the health monitoring algorithm via controlled accelerated deterioration of magnetization in the PMSM. The performance of the proposed algorithm has been compared with that of a classical motor current signature analysis (MCSA) procedure as well as with a benchmark particle filter for fault detection in PMSMs.

    AB - This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation of the PMSM. The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault. A special-purpose test bed has been designed and fabricated for experimental validation of the health monitoring algorithm via controlled accelerated deterioration of magnetization in the PMSM. The performance of the proposed algorithm has been compared with that of a classical motor current signature analysis (MCSA) procedure as well as with a benchmark particle filter for fault detection in PMSMs.

    UR - http://www.scopus.com/inward/record.url?scp=84871725765&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84871725765&partnerID=8YFLogxK

    U2 - 10.1016/j.epsr.2012.11.005

    DO - 10.1016/j.epsr.2012.11.005

    M3 - Article

    AN - SCOPUS:84871725765

    VL - 96

    SP - 225

    EP - 236

    JO - Electric Power Systems Research

    JF - Electric Power Systems Research

    SN - 0378-7796

    ER -