Few-Shot Cross-Domain Fault Diagnosis of Bearing Driven by Task-Supervised ANIL
Author:
Affiliation:
1. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China
2. Department of Management Science, University of Strathclyde, Glasgow, U.K.
Funder
National Natural Science Foundation of China
Science and Technology Innovation Program of Hunan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6488907/10570342/10418185.pdf?arnumber=10418185
Reference33 articles.
1. Cross-domain intelligent bearing fault diagnosis under class imbalanced samples via transfer residual network augmented with explicit weight self-assignment strategy based on meta data
2. Edge Computing on IoT for Machine Signal Processing and Fault Diagnosis: A Review
3. Optimization of Edge-PLC-Based Fault Diagnosis With Random Forest in Industrial Internet of Things
4. Fast and Accurate Deep Learning Framework for Secure Fault Diagnosis in the Industrial Internet of Things
5. Fault diagnosis method of planetary gearbox based on empirical mode decomposition and deep convolutional neural network;Niaoqing;J. Mech. Eng. (In Chinese),2019
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