An improved multi-channel graph convolutional network and its applications for rotating machinery diagnosis
Published 2022 View Full Article
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Title
An improved multi-channel graph convolutional network and its applications for rotating machinery diagnosis
Authors
Keywords
Multi-channel graph convolutional network, Fault diagnosis, Graph feature learning, Multi-sensor data
Journal
MEASUREMENT
Volume 190, Issue -, Pages 110720
Publisher
Elsevier BV
Online
2022-01-10
DOI
10.1016/j.measurement.2022.110720
References
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Related references
Note: Only part of the references are listed.- Rolling bearing fault diagnosis with combined convolutional neural networks and support vector machine
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- Dynamic Graph-Based Feature Learning With Few Edges Considering Noisy Samples for Rotating Machinery Fault Diagnosis
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- Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes
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- EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks
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