Bearing Fault diagnosis based on convolution Neural Network with Multi-Attention Mechanism
Author:
Affiliation:
1. China Three Gorges University,College of Mechanical and Power Engineering,Yichang,Hubei,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10246450/10246476/10246662.pdf?arnumber=10246662
Reference10 articles.
1. New fusion features convolutional neural network with high generalization ability on rolling bearing fault diagnosis
2. Bearing fault diagnosis base on multi-scale CNN and LSTM model
3. A novel attention-based domain adaptation model for intelligent bearing fault diagnosis under variable working conditions[J];wang;Measurement Science and Technology,2021
4. Network Construction for Bearing Fault Diagnosis Based on Double Attention Mechanism
5. Feature Mining and Sensitivity Analysis with Adaptive Sparse Attention for Bearing Fault Diagnosis
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1. Bearing Fault Diagnosis Method Based on Multi-scale Dilated Convolution Under Various Noise Conditions;Mechanisms and Machine Science;2024
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