Multichannel Vibration Signal Fusion Based on Rolling Bearings and MRST-Transformer Fault Diagnosis Model-Reference-Cited by-同舟云学术

Multichannel Vibration Signal Fusion Based on Rolling Bearings and MRST-Transformer Fault Diagnosis Model

Published:2024-05-15 Issue:10 Volume:24 Page:16336-16346
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wu Xiaoguang¹^ORCID,Peng Huadong²^ORCID,Cui Xingyue²,Guo Tianwen³,Zhang Yating²^ORCID

Affiliation:

1. School of Computer and Information Engineering and the Department of Electronic Information Engineering, Nanjing Tech University, Nanjing, Jiangsu, China

2. School of Computer and Information Engineering, Nanjing Tech University, Nanjing, Jiangsu, China

3. Experimental Center, School of Computer and Information Engineering, Nanjing Tech University, Nanjing, Jiangsu, China

Funder

2023 Jiangsu Province Graduate Practice and Innovation Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10530892/10496526.pdf?arnumber=10496526

Reference36 articles.

1. A review on empirical mode decomposition in fault diagnosis of rotating machinery

2. Bearing Fault Diagnosis under Variable Speed Using Convolutional Neural Networks and the Stochastic Diagonal Levenberg-Marquardt Algorithm

3. Statistical Spectral Analysis for Fault Diagnosis of Rotating Machines

4. Tacho-less sparse CNN to detect defects in rotor-bearing systems at varying speed

5. GAN-Based Bearing Fault Diagnosis Method for Short and Imbalanced Vibration Signal

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