Multiphysical modeling for fault detection in Permanent Magnet Synchronous Motors

Alameh, Kawthar; Cité, Nicolas; Hoblos, Ghaleb; Barakat, Georges

doi:10.1109/icit.2015.7125193

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…For this reason, an improved analytical approach has been used to calculate them, taking into account the entire stator structure with teeth and winding [11]. Analytical results have been validated by a Tow-Dimensional (2-D) FEA using ANSYS software, for different circumferential modes.…”

Section: B Mechanical Modelmentioning

confidence: 99%

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Feature extraction for vibration-based fault detection in Permanent Magnet Synchronous Motors

Alameh¹,

Cité²,

Hoblos³

et al. 2015

2015 Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE)

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this paper presents a study of different time and frequency indicators, extracted from vibration signals of a Permanent Magnet Synchronous Machine (PMSM), for fault detection and diagnosis purpose. First, a multi-physical model of the machine, able to generate the vibration displacement under different operating conditions, is simulated. Then, a brief stateof-the-art on the most encountered machine faults, with their electromagnetic and mechanical signatures, is presented. In this study, both rotor eccentricity and Permanent Magnet (PM) demagnetization faults are considered and introduced in the model by changing some of its parameters. After that, time-and frequency-domains signal processing techniques are applied to extract crucial features sets, related to healthy and faulty cases, from vibration signals. The evolution of these indicators with respect to faults degrees is analyzed to select proper criteria for each one, which can be effectively used latter in fault detection and diagnosis applications.

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Section: B Mechanical Modelmentioning

confidence: 99%

“…A 24-slot four-pole PMSM, with parameters listed in Appendix A in [11], has been used as a reference motor. It is driven by a 3-phase current at constant frequency (50 Hz).…”

Section: B Mechanical Modelmentioning

confidence: 99%

Feature extraction for vibration-based fault detection in Permanent Magnet Synchronous Motors

Alameh¹,

Cité²,

Hoblos³

et al. 2015

2015 Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE)

Self Cite

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show abstract

“…Results showed that they demonstrated the accuracy of the method they proposed. Alameh et al [14] carried out studies on the detection of eccentricity faults in PMSMs. They presented an analytical multiphysical model.…”

Section: Eccentricity Faults In Pmsmsmentioning

confidence: 99%

Eccentricity fault diagnosis in a permanent magnet synchronous motor under nonstationary speed conditions

Eker¹,

Akar²

2017

Turk J Elec Eng & Comp Sci

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Electric motor faults decrease production capacity and increase maintenance costs. Today, predictive detection based on real-time monitoring and fault detection is taking the place of periodic applications. In this study, a new method is presented for the detection of eccentricity faults in permanent magnet synchronous motors. The motor current and the rotor speed were monitored under stationary and nonstationary speed and different load conditions, after which the fault detection was carried out via angular domain-order tracking method. The obtained results were compared with traditional fast Fourier transform results. It was observed that the suggested method can successfully detect the fault for stationary and nonstationary signals. In addition, the position of the fault-related components are constant independent of the motor current frequency, speed, and load levels.

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Discrimination between demagnetization and eccentricity faults in PMSMs using real and imaginary components of stator current spectral analysis

et al. 2020

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Multiphysical modeling for fault detection in Permanent Magnet Synchronous Motors

Cited by 6 publications

References 13 publications

Feature extraction for vibration-based fault detection in Permanent Magnet Synchronous Motors

Feature extraction for vibration-based fault detection in Permanent Magnet Synchronous Motors

Eccentricity fault diagnosis in a permanent magnet synchronous motor under nonstationary speed conditions

Discrimination between demagnetization and eccentricity faults in PMSMs using real and imaginary components of stator current spectral analysis

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