Fusion of Variational Modal Decomposition and ResNet Network for Intelligent Fault Diagnosis of the Bearing under Time-varying Speed Condition-Reference-Cited by-同舟云学术

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Fusion of Variational Modal Decomposition and ResNet Network for Intelligent Fault Diagnosis of the Bearing under Time-varying Speed Condition

Published:2023-11-03 Issue: Volume: Page:304-309
ISSN:
Container-title:2023 2nd International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE)
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Author:

Xing Yitong¹,Yao Yu²,Wang Bowen²,Zhang Cuiling³

Affiliation:

1. Ningxia Institute of Science and Technology,School of Electrical Information Engineering,Shizuishan,China

2. Northeastern University,The College of Information Science and Engineering,Shenyang,China

3. Ningxia Institute of Science and Technology,Innovation and Entrepreneurship,Shizuishan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10438942/10439070/10439119.pdf?arnumber=10439119

Reference12 articles.

1. A Novel Data-Driven Fault Feature Separation Method and Its Application on Intelligent Fault Diagnosis Under Variable Working Conditions

2. Adaptive fast Chirplet transform and its application into fault diagnosis of rolling bearing under time-varying speed condition

3. Improved Rotating Speed Estimation and Bearing Fault Diagnosis Using Multi-Channel Vibration Signals

4. CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery

5. A Multisource Dense Adaptation Adversarial Network for Fault Diagnosis of Machinery

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