Multisensor-Driven Cross-Domain Motor Fault Diagnosis Based on Multibasis Energy Pattern
Author:
Affiliation:
1. College of Electrical and Information Engineering, Hunan University, Changsha, China
2. College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
Funder
National Nature Science Foundation of China
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10235271/10186341.pdf?arnumber=10186341
Reference30 articles.
1. Fault Diagnosis Method of Low-Speed Rolling Bearing Based on Acoustic Emission Signal and Subspace Embedded Feature Distribution Alignment
2. A New Cross-Domain Bearing Fault Diagnosis Framework Based on Transferable Features and Manifold Embedded Discriminative Distribution Adaption Under Class Imbalance
3. Unsupervised domain adaptation via enhanced transfer joint matching for bearing fault diagnosis
4. Balanced Adaptation Regularization Based Transfer Learning for Unsupervised Cross-Domain Fault Diagnosis
5. Fault diagnosis of rolling bearing using symmetrized dot pattern and density-based clustering
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