Vibration States Detection of HTS Pinning Maglev System Based on Deep Learning Algorithm-Reference-Cited by-同舟云学术

Vibration States Detection of HTS Pinning Maglev System Based on Deep Learning Algorithm

Published:2022-09 Issue:6 Volume:32 Page:1-6
ISSN:1051-8223
Container-title:IEEE Transactions on Applied Superconductivity
language:
Short-container-title:IEEE Trans. Appl. Supercond.

Author:

Ke Zhihao¹^ORCID,Deng Zigang¹^ORCID,Chen Yining²,Yi Huiyang³,Liu Xiaoning¹^ORCID,Wang Li¹^ORCID,Zhang Penghui¹^ORCID,Ren Tianci¹^ORCID

Affiliation:

1. State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu, China

2. Leeds-Joint School, Southwest Jiaotong University, Chengdu, China

3. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

Funder

National Natural Science Foundation of China

Sichuan Science and Technology Program

Fundamental Research Funds for the Central Universities

Foundation of Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle

Ministry of Education, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

http://xplorestaging.ieee.org/ielx7/77/9712164/09765350.pdf?arnumber=9765350

Reference21 articles.

1. Attenuation of Levitation Performance for Side-Suspending HTS Maglev System Under Vibration

2. Effect of Eddy Current Damper on the Dynamic Vibration Characteristics of High-Temperature Superconducting Maglev System

3. Soft computing methods applied to train station parking in urban rail transit

4. Route recommendation algorithm for railway transit travelers based on classification of personal characteristics;hong;Proc Int Conf Inf Syst Manage Eng,0

5. Software and machine learning tools for monitoring railway track switch performance

Cited by 5 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. Enhancing the Predictive Modeling of n-Value Surfaces in Various High Temperature Superconducting Materials Using a Feed-Forward Deep Neural Network Technique;Crystals;2024-07-05

2. Estimation of magnetic levitation and lateral forces in MgB₂ superconducting bulks with various dimensional sizes using artificial intelligence techniques;Superconductor Science and Technology;2024-06-07

3. Nonlinear Levitation-Guidance Coupling Force Prediction for HTS Pinning Maglev Under Arbitrary Motion Based on Gated Recurrent Unit;IEEE Transactions on Applied Superconductivity;2024-05

4. Machine learning driven optimization and parameter selection of multi-surface HTS Maglev;Physica C: Superconductivity and its Applications;2024-01

5. Magnetic force prediction of hybrid magnet with Halbach array using generalized regression neural network optimized by a modified aquila optimizer;International Journal of Applied Electromagnetics and Mechanics;2023-01-27