Bearing Fault Diagnosis in Permanent Magnet Synchronous Machine Based on Signature Analysis of Encoder Signal Under Variable Speed Conditions

A signature analysis method of encoder signal is investigated in this paper for bearing fault diagnosis of a permanent magnet synchronous machines (PMSMs) under variable speed conditions. Firstly, the rotor speed and angle signal, which contain the fault feature harmonic and accumulative rotation angle information, are obtained from the encoder signal. Besides, the fault feature harmonic can be accurately extracted from rotor speed and the accumulative angle is calculated by encoder signal. Finally, the time-domain rotor speed is resampled to the angular domain, and the type of bearing fault is then diagnosed via the envelope spectrum of the resampled signal. In this article, the diagnostic performance of the proposed method is validated on the PMSMs that are equipped with outer and inner race fault bearings under variable speed conditions. Besides, its superiority under dynamic speed conditions is also demonstrated, compared with the existing solutions.

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Publication Details

Journal
IEEE Transactions on Energy Conversion
Published
2024-10-24
DOI
https://doi.org/10.1109/tec.2024.3486009
Citations
2
Primary Topic
Engineering Diagnostics and Reliability
Type
article
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0.54
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article

Bearing Fault Diagnosis in Permanent Magnet Synchronous Machine Based on Signature Analysis of Encoder Signal Under Variable Speed Conditions

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article

Bearing Fault Diagnosis in Permanent Magnet Synchronous Machine Based on Signature Analysis of Encoder Signal Under Variable Speed Conditions

Jinya Chen, Kaiqing Li, Yongdan Chen, Haozhe Luan, Shichao Zhou, Renping Li, Jianbo Wang, Dong Wei, Kan Liu
article en
2 citations

Abstract

A signature analysis method of encoder signal is investigated in this paper for bearing fault diagnosis of a permanent magnet synchronous machines (PMSMs) under variable speed conditions. Firstly, the rotor speed and angle signal, which contain the fault feature harmonic and accumulative rotation angle information, are obtained from the encoder signal. Besides, the fault feature harmonic can be accurately extracted from rotor speed and the accumulative angle is calculated by encoder signal. Finally, the time-domain rotor speed is resampled to the angular domain, and the type of bearing fault is then diagnosed via the envelope spectrum of the resampled signal. In this article, the diagnostic performance of the proposed method is validated on the PMSMs that are equipped with outer and inner race fault bearings under variable speed conditions. Besides, its superiority under dynamic speed conditions is also demonstrated, compared with the existing solutions.

IEEE Transactions on Energy ConversionVol. 40(2)
Hunan University (CN)
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Openalex Percentile: Top 39%
Engineering Diagnostics and Reliability
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