A rolling bearing fault diagnosis model based on WCNN-BiGRU
Author:
Affiliation:
1. Southwest University of Science and Technology,School of Information Engineering,Mianyang,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9727224/9727236/09728363.pdf?arnumber=9728363
Reference12 articles.
1. A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals[J];wei;SENSORS,2017
2. Deep Learning based End-to-End Rolling Bearing Fault Diagnosis
3. Semi-random subspace with Bi- GRU: Fusing statistical and deep representation features for bearing fault diagnosis[J];mao;Measurement,2020
4. Early Fault Detection Method of Rolling Bearing Based on MCNN and GRU Network with an Attention Mechanism
5. Application of BP Neural Network and Convolutional Neural Network (CNN) in Bearing Fault Diagnosis
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1. Electricity theft detection in smart grid using machine learning;Frontiers in Energy Research;2024-03-20
2. A Bearing Fault Diagnosis Method Based on Dilated Convolution and Multi-Head Self-Attention Mechanism;Applied Sciences;2023-11-28
3. Rolling Bearing Fault Diagnosis Method Based on Attention CNN and BiLSTM Network;Neural Processing Letters;2022-10-05
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