High-Speed Bearing Health Monitoring Method Based on Attention Mechanism Optimized Siamese Deep Residual Network
Author:
Affiliation:
1. School of Mechanical Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
2. School of Mechanical Engineering, Hubei University of Technology, Wuhan, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Key-Area Research and Development Program of Hubei Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10269339/10233215.pdf?arnumber=10233215
Reference45 articles.
1. Sparse dictionary design based on edited cepstrum and its application in rolling bearing fault diagnosis
2. Fast Calculation of Broadband Battery Impedance Spectra Based on S Transform of Step Disturbance and Response
3. Bearing remaining useful life prediction using self-adaptive graph convolutional networks with self-attention mechanism
4. The identities of n-dimensional s-transform and applications
5. Enhanced deep residual network with multilevel correlation information for fault diagnosis of rotating machinery
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