Bearing Fault Image Classification Method Based on Interpretable Hyperparameter Optimization Model
Author:
Affiliation:
1. Qixin Honors School, Zhejiang Sci-Tech University,Hangzhou,China
2. Tongji University, Sino-german School of Engineering,Shanghai,China
3. Detroit Green Technology Institute, Hubei University of Technology,Wuhan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10545644/10545608/10545905.pdf?arnumber=10545905
Reference10 articles.
1. An Adaptive Optimized TVF-EMD Based on a Sparsity-Impact Measure Index for Bearing Incipient Fault Diagnosis
2. An EMD-LSTM-SVR model for the short-term roll and sway predictions of semi-submersible
3. An integrated method based on hybrid grey wolf optimizer improved variational mode decomposition and deep neural network for fault diagnosis of rolling bearing
4. Method of fault feature selection and fusion based on poll mode and optimized weighted KPCA for bearings
5. A Tensor-based domain alignment method for intelligent fault diagnosis of rolling bearing in rotating machinery
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