Modeling and detecting the stator winding inter turn fault of permanent magnet synchronous motors using stator current signature analysis

N. Yassa and M. Rachek

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 167, issue C, 325-339

Abstract: Many researchers have been attracted by the challenges of electrical machines fault detection, diagnosis and monitoring, which provide early warning that could help schedule necessary maintenance to avoid catastrophic consequence. Considerable papers have presented reviews and compared conditions monitoring and fault diagnosis methods for induction machines, but none for permanent magnet machines. In this paper a dynamic fault model for a rotor surface mounted PMSM machine under inter-turn insulation failure is derived. this model allows to study the location and severity of the stator winding fault using electrical circuit magnetically coupled. To achieve this objective, a precise mathematical model that can describe both healthy and fault conditions is developed. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, power spectral density (PSD) was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM.

Keywords: Diagnosis; SPMSM; Short circuit; Motor current signature analysis (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:167:y:2020:i:c:p:325-339

DOI: 10.1016/j.matcom.2018.04.012

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