Semi-Supervised Multiscale Permutation Entropy-Enhanced Contrastive Learning for Fault Diagnosis of Rotating Machinery
Author:
Affiliation:
1. College of Mechanical and Electrical Engineering, Jiaxing Nanhu University, Jiaxing, China
2. College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, China
Funder
National Natural Science Foundation of China
Zhejiang Provincial Natural Science Foundation of China
Wenzhou Key Innovation Project for Science and Technology of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10203049.pdf?arnumber=10203049
Reference28 articles.
1. A novel tool condition monitoring based on Gramian angular field and comparative learning
2. Development of LDA Based Indicator for the Detection of Unbalance and Misalignment at Different Shaft Speeds
3. Dimensionality Reduction by Learning an Invariant Mapping
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