Demagnetization Fault Detection and Location in PMSM Based on Correlation Coefficient of Branch Current Signals

Yinquan Yu, Haixi Gao, Qiping Chen, Peng Liu and Shuangxia Niu
Additional contact information
Yinquan Yu: School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Haixi Gao: School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Qiping Chen: School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Peng Liu: School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China
Shuangxia Niu: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China

Energies, 2022, vol. 15, issue 8, 1-17

Abstract: To address such challenges as an uncertain number of demagnetization poles of the permanent magnet synchronous motor (PMSM) and cases in which the fault cannot be located, this paper proposes a fault identification and location methodology based on the analysis of the motor stator current. First, the influence of the irreversible demagnetization of permanent magnets on the analytical model of the back electromotive force (Back-EMF) of the rotor in a single motor stator slot is analyzed. Moreover, considering the topology of the motor, the influence of the demagnetization fault on the stator phase current and branch current is analyzed. Since the stator phase currents cannot diagnose the partial demagnetization faults of PMSM with some topological structures, the stator branch current is selected as the signal for the identification and localization of the demagnetization fault. Secondly, the demagnetization fault diagnosis and mode recognition of the motor are carried out through the amplitude of the real-time branch current and the harmonic components of the PMSM. A sample database of demagnetization faults is established through calculation and normalization of the residual value of the stator branch current and the branch current of the healthy motor after demagnetization in one pole order. The fault threshold is obtained by analyzing the residual of the branch current of uniform demagnetization and the Pearson correlation coefficient of the fault sample database. Then, the correlation coefficient between the real-time branch current residual value of PMSM and the fault sample database is analyzed, and the number of demagnetization poles and the fault location are determined by the number and location of the calculated correlation coefficient exceeding the threshold. Finally, the feasibility and effectiveness of the proposed method are verified by the finite element analysis (FEA) results.

Keywords: PMSM; demagnetization fault detection and location; stator branch current; Pearson correlation coefficient; fault sample database (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/8/2952/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/8/2952/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:8:p:2952-:d:796077

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().