A Transferability-Enhanced and Structural Information Mining Network for Cross-Domain Fault Diagnosis
Author:
Affiliation:
1. College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China
2. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Postdoctoral Fellow-ship Program of China Postdoctoral Science Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/7361/10577556/10539625.pdf?arnumber=10539625
Reference36 articles.
1. Multi-Scale Stochastic Resonance Spectrogram for fault diagnosis of rolling element bearings
2. Flexible Generalized Demodulation for Intelligent Bearing Fault Diagnosis Under Nonstationary Conditions
3. Sparse discriminant manifold projections for bearing fault diagnosis
4. A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication
5. Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes
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