Degradation State Analysis of Permanent Magnet Synchronous Motor Winding Based on Multiscale Multidimensional Correlated Sample Entropy

In this article, a degradation model for the permanent magnet synchronous machine (PMSM) windings is carried out based on multiscale multidimensional correlated sample entropy (MMCSE). First, the calculation process of multiscale sample entropy (mse) is optimized to extend its applicability from 1-D data to multidimensional data. Next, the range of analysis scales is determined, and the degradation model of the PMSM winding is established based on entropy values under degradation and healthy states. Then, the simulation models of the PMSM under different degradation states are constructed, and the important parameters of the algorithm are determined using the Jellyfish optimization algorithm. Finally, the experiments are presented to validate the accuracy of simulation analysis. The research results indicate that the degradation model based on MMCSE can accurately determine whether the PMSM windings have experienced performance degradation. The calculation results of the degradation model are related to machine reliability, providing a new quantitative evaluation metric for assessing changes in the PMSM reliability.

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Publication Details

Journal
IEEE Journal of Emerging and Selected Topics in Power Electronics
Published
2024-09-30
DOI
https://doi.org/10.1109/jestpe.2024.3470125
Primary Topic
Non-Destructive Testing Techniques
Type
article
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article

Degradation State Analysis of Permanent Magnet Synchronous Motor Winding Based on Multiscale Multidimensional Correlated Sample Entropy

Shichuan Ding, Wei Li, Yu xiang Wu, Puzheng Liu
IEEE Journal of Emerging and Selected Topics in Power Electronics
Non-Destructive Testing Techniques
article

Degradation State Analysis of Permanent Magnet Synchronous Motor Winding Based on Multiscale Multidimensional Correlated Sample Entropy

Shichuan Ding, Wei Li, Yu xiang Wu, Puzheng Liu
article en

Abstract

In this article, a degradation model for the permanent magnet synchronous machine (PMSM) windings is carried out based on multiscale multidimensional correlated sample entropy (MMCSE). First, the calculation process of multiscale sample entropy (mse) is optimized to extend its applicability from 1-D data to multidimensional data. Next, the range of analysis scales is determined, and the degradation model of the PMSM winding is established based on entropy values under degradation and healthy states. Then, the simulation models of the PMSM under different degradation states are constructed, and the important parameters of the algorithm are determined using the Jellyfish optimization algorithm. Finally, the experiments are presented to validate the accuracy of simulation analysis. The research results indicate that the degradation model based on MMCSE can accurately determine whether the PMSM windings have experienced performance degradation. The calculation results of the degradation model are related to machine reliability, providing a new quantitative evaluation metric for assessing changes in the PMSM reliability.

IEEE Journal of Emerging and Selected Topics in Power ElectronicsVol. 13(2)
Anhui University (CN)
Affordable and clean energy
Openalex Percentile: Top 84%
Non-Destructive Testing Techniques
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Degradation State Analysis of Permanent Magnet Synchronous Motor Winding Based on Multiscale Multidimensional Correlated Sample Entropy — Shichuan Ding, Wei Li, et al. · IEEE Journal of Emerging and Selected Topics in Power Electronics (2024) | TGRS Research Map | TGRS