Fast Online Fault Diagnosis for PMSM Based on Adaptation Model-Reference-Cited by-同舟云学术

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Fast Online Fault Diagnosis for PMSM Based on Adaptation Model

Published:2024-08-01 Issue:15 Volume:24 Page:24319-24327
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Hu Huanan¹^ORCID,Gao Jingwei²,Zhang Xiangpo³,Zhang Xiaofei¹^ORCID,Qu Yinpeng¹^ORCID,Qin Guojun¹^ORCID,Liu Qiang¹^ORCID

Affiliation:

1. College of Electrical and Information Engineering, Hunan University, Changsha, China

2. College of Air and Space Science, National University of Defense Technology, Changsha, China

3. Field Engineering College, Army Engineering University of PLA, Nanjing, China

Funder

Science Fund for Distinguished Young Scholars of Hunan

National Natural Science Foundation of China

National Key Research and Development Program of China

Key Research and Development Program of Hunan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7361/10617804/10566612.pdf?arnumber=10566612

Reference30 articles.

1. Interturn Short Fault Diagnosis in a PMSM by Voltage and Current Residual Analysis With the Faulty Winding Model

2. Compressed Channel-Based Edge Computing for Online Motor Fault Diagnosis With Privacy Protection

3. Multisource Unsupervised Subdomain Adaptation Network for Rotary Machine Fault Diagnosis

4. Online Diagnosis and Severity Estimation of Partial and Uniform Irreversible Demagnetization Fault in Interior Permanent Magnet Synchronous Motor

5. Infrared Thermography-Based Fault Diagnosis of Induction Motor Bearings Using Machine Learning

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