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
Y1 - 2013
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.
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U2 - 10.1016/j.epsr.2012.11.005
DO - 10.1016/j.epsr.2012.11.005
M3 - Article
AN - SCOPUS:84871725765
SN - 0378-7796
VL - 96
SP - 225
EP - 236
JO - Electric Power Systems Research
JF - Electric Power Systems Research
ER -