This paper studies the effects of static eccentricity (SE) in Flux Switching Permanent Magnet (FSPM) Machines to propose a criterion for fault detection. SE is one of the most common mechanical faults in electrical machines on. In order to achieve this goal, the proposed machine is studied under different degrees of static eccentricity fault to analyze machine condition. Finite element modeling (FEM) as the most accurate numerical approach is used to obtain precise results. The magnetic flux distribution of rotor and stator are calculated. In addition, air-gap flux density as a parameter which has a direct impact on back-EMF is assessed by using finite element analysis (FEA). It is found that static eccentricity has noticeable influences on back-EMF of coils of the machine. Furthermore, Fourier analysis is performed in order to achieve appropriate index for the diagnosis process. The results are provided for the healthy machine and the machine with different values of SE and the proposed index has been derived for the fault detection process in the machine.

Static eccentricity fault detection in Flux Switching Permanent Magnet machines

MARIGNETTI, Fabrizio;
2016-01-01

Abstract

This paper studies the effects of static eccentricity (SE) in Flux Switching Permanent Magnet (FSPM) Machines to propose a criterion for fault detection. SE is one of the most common mechanical faults in electrical machines on. In order to achieve this goal, the proposed machine is studied under different degrees of static eccentricity fault to analyze machine condition. Finite element modeling (FEM) as the most accurate numerical approach is used to obtain precise results. The magnetic flux distribution of rotor and stator are calculated. In addition, air-gap flux density as a parameter which has a direct impact on back-EMF is assessed by using finite element analysis (FEA). It is found that static eccentricity has noticeable influences on back-EMF of coils of the machine. Furthermore, Fourier analysis is performed in order to achieve appropriate index for the diagnosis process. The results are provided for the healthy machine and the machine with different values of SE and the proposed index has been derived for the fault detection process in the machine.
2016
978-1-5090-2067-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/62444
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