LAPSE:2023.21670
Published Article

LAPSE:2023.21670
Inter-turn Fault Identification of Surface-Mounted Permanent Magnet Synchronous Motor Based on Inverter Harmonics
March 22, 2023
Abstract
Inter-turn short-circuit faults can lead to further faults in motors. This makes monitoring and identifying such faults particularly important. However, because of interference in their working environment, fault signals can be weak and difficult to detect in permanent magnet synchronous motors. This paper proposes a method for overcoming this by extracting the inverter harmonics as an excitation source and then extracting characteristic of fault measurements from the negative sequence voltage. First of all, a model of permanent magnet synchronous motor faults is established and a fault negative sequence voltage is introduced to calculate the fault indicators. Then the high frequency harmonic excitation in the voltage is extracted. This is injected into the original voltage signal and the high frequency negative sequence component is separated and detected by a second-order generalized integrator. Simulation results show that the proposed method can effectively identify inter-turn short-circuit faults in permanent magnet synchronous motors while remaining highly resistant to interference. The method is especially effective when the severity of the fault is relatively small and the torque is relatively large.
Inter-turn short-circuit faults can lead to further faults in motors. This makes monitoring and identifying such faults particularly important. However, because of interference in their working environment, fault signals can be weak and difficult to detect in permanent magnet synchronous motors. This paper proposes a method for overcoming this by extracting the inverter harmonics as an excitation source and then extracting characteristic of fault measurements from the negative sequence voltage. First of all, a model of permanent magnet synchronous motor faults is established and a fault negative sequence voltage is introduced to calculate the fault indicators. Then the high frequency harmonic excitation in the voltage is extracted. This is injected into the original voltage signal and the high frequency negative sequence component is separated and detected by a second-order generalized integrator. Simulation results show that the proposed method can effectively identify inter-turn short-circuit faults in permanent magnet synchronous motors while remaining highly resistant to interference. The method is especially effective when the severity of the fault is relatively small and the torque is relatively large.
Record ID
Keywords
fault identification, inter-turn short-circuit fault, inverter harmonics, negative sequence voltage, permanent magnet synchronous motor
Subject
Suggested Citation
Gao F, Zhang G, Li M, Gao Y, Zhuang S. Inter-turn Fault Identification of Surface-Mounted Permanent Magnet Synchronous Motor Based on Inverter Harmonics. (2023). LAPSE:2023.21670
Author Affiliations
Gao F: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China [ORCID]
Zhang G: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Li M: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Gao Y: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Zhuang S: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Zhang G: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Li M: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Gao Y: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Zhuang S: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Journal Name
Energies
Volume
13
Issue
4
Article Number
E899
Year
2020
Publication Date
2020-02-18
ISSN
1996-1073
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Original Submission
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PII: en13040899, Publication Type: Journal Article
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LAPSE:2023.21670
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https://doi.org/10.3390/en13040899
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Mar 22, 2023
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