PMSLM Eccentricity Fault Diagnosis Based on Deep Feature Fusion of Stray Magnetic Field Signals-Reference-Cited by-同舟云学术

PMSLM Eccentricity Fault Diagnosis Based on Deep Feature Fusion of Stray Magnetic Field Signals

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Song Juncai¹^ORCID,Wu Xianhong²^ORCID,Qian Long²^ORCID,Lv Wenjun³^ORCID,Wang Xiaoxian⁴^ORCID,Lu Siliang²^ORCID

Affiliation:

1. College of Internet, Anhui University, Hefei, China

2. College of Electrical Engineering and Automation, Anhui University, Hefei, China

3. Department of Automation, University of Science and Technology of China, Hefei, China

4. College of Electronics and Information Engineering, Anhui University, Hefei, China

Funder

National Natural Science Foundation of China

Anhui Provincial Natural Science Foundation

Project of the Outstanding Young Talents in Colleges and Universities of Anhui Province

College Natural Science Research Key project of Anhui Education Department

University Outstanding Youth Research Project of Anhui Province

University Synergy Innovation Program of Anhui Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10373088.pdf?arnumber=10373088

Reference43 articles.

1. Efficient Optimization Design Method of PMSLM Based on Deep Adaptive Ridge Regression with Embedded Analytical Mapping Function

2. Thrust Performance Improvement of PMSLM Based on Lasso Regression With Embedded Analytical Model

3. Performance Analysis of a New Type PM-Resolver in Healthy and Eccentric Cases by an Improved Parametric MEC Method

4. Dynamic air gap asymmetry fault detection in single‐sided linear induction motors

5. Diagnosis of simultaneous broken rotor bars and static eccentricity faults of induction motors by analyzing stator current and vibration signals;Kabul;J. Fac. Eng. Archit. Gazi Univ.,2021

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DPMSLM Eccentricity Fault Detection Based on Multiview of Mystery Curve Transformation and Deep Feature Extraction;IEEE Sensors Journal;2024-06-01

2. Multisource Deep Feature Fusion of Optimized Symmetrized Dot Patterns for SRM Fault Diagnosis;IEEE Transactions on Instrumentation and Measurement;2024