Bearing Fault Diagnosis Using Convolutional Sparse Representation Combined With Nonlocal Similarity
Author:
Affiliation:
1. Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education, School of Electrical Engineering and Automation, Anhui University, Hefei, China
Funder
Natural Science Foundation of Anhui
Key Science Program of Anhui Education Department
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10068826/10017191.pdf?arnumber=10017191
Reference30 articles.
1. A recursive sparse representation strategy for bearing fault diagnosis
2. Compound Fault Diagnosis Using Optimized MCKD and Sparse Representation for Rolling Bearings
3. Nonconvex Sparse Regularization and Convex Optimization for Bearing Fault Diagnosis
4. Bearing fault diagnosis via generalized logarithm sparse regularization
5. Preprocessing-Free Gear Fault Diagnosis Using Small Datasets With Deep Convolutional Neural Network-Based Transfer Learning
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