<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In modern drive systems, the high-efficient permanent magnet synchronous motors (PMSMs) have become one of the most substantial components. Nevertheless, such machines are exposed to various types of faults. Hence, on-line condition monitoring and fault diagnosis of PMSMs have become necessary. One of the most common PMSM faults is the stator winding fault. Due to the destructive character of this failure, it is necessary to use fault diagnostic methods that allow fault detection at its early stage. The article presents the results of experimental studies obtained from fast Fourier transform (FFT) and short-time Fourier transform (STFT) analyses of the stator phase current, stator phase current envelope and stator phase current space vector module. The superiority of the proposed method over the classical approach based on the stator current analysis using FFT is highlighted. The proposed solution is experimentally verified under various motor operating conditions. The application of STFT analysis discussed so far in the literature has been limited to the fault diagnosis of induction motors and the narrow range of the analysed motor operating conditions. Moreover, there are no works in the field of motor diagnostics dealing with STFT analysis for stator windings based on the stator current envelope and the stator current space vector module.</p>
</abstract>

In modern drive systems, the high-efficient permanent magnet synchronous motors (PMSMs) have become one of the most substantial components. Nevertheless, such machines are exposed to various types of faults. Hence, on-line condition monitoring and fault diagnosis of PMSMs have become necessary. One of the most common PMSM faults is the stator winding fault. Due to the destructive character of this failure, it is necessary to use fault diagnostic methods that allow fault detection at its early stage. The article presents the results of experimental studies obtained from fast Fourier transform (FFT) and short-time Fourier transform (STFT) analyses of the stator phase current, stator phase current envelope and stator phase current space vector module. The superiority of the proposed method over the classical approach based on the stator current analysis using FFT is highlighted. The proposed solution is experimentally verified under various motor operating conditions. The application of STFT analysis discussed so far in the literature has been limited to the fault diagnosis of induction motors and the narrow range of the analysed motor operating conditions. Moreover, there are no works in the field of motor diagnostics dealing with STFT analysis for stator windings based on the stator current envelope and the stator current space vector module.

Stator Winding Fault Detection of Permanent Magnet Synchronous Motors Based on the Short-Time Fourier Transform

Wrocław University of Science and Technology

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

In modern drive systems, the high-efficient permanent magnet synchronous motors (PMSMs) have become one of the most substantial components. Nevertheless, such...

Stator Winding Fault Detection of Permanent Magnet Synchronous Motors Based on the Short-Time Fourier Transform

Data publikacji: 30 cze 2022

Zakres stron: 112 - 133

Otrzymano: 05 maj 2022

Przyjęty: 02 cze 2022

DOI: https://doi.org/10.2478/pead-2022-0009

Słowa kluczowe
faults diagnosis, condition monitoring, inter-turn short circuit, permanent magnet synchronous motor, short-time Fourier transform

© 2022 Przemysław Pietrzak et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Stator Winding Fault Detection of Permanent Magnet Synchronous Motors Based on the Short-Time Fourier Transform

Data publikacji: 30 cze 2022

Zakres stron: 112 - 133

Otrzymano: 05 maj 2022

Przyjęty: 02 cze 2022

DOI: https://doi.org/10.2478/pead-2022-0009

Słowa kluczowefaults diagnosis, condition monitoring, inter-turn short circuit, permanent magnet synchronous motor, short-time Fourier transform

© 2022 Przemysław Pietrzak et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
faults diagnosis, condition monitoring, inter-turn short circuit, permanent magnet synchronous motor, short-time Fourier transform