Noise-Boosted Convolutional Neural Network for Edge-based Motor Fault Diagnosis with Limited Samples
Author:
Affiliation:
1. College of Electrical Engineering and Automation, Anhui University, Hefei, China
2. Beijing Research Institute of Mechanical & Electrical Technology, Beijing, China
3. Department of Engineering, Lancaster University, Lancaster, U.K.
Funder
National Natural Science Foundation of China
Project of the Outstanding Young Talents in Colleges and Universities of Anhui Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9424/4389054/09983497.pdf?arnumber=9983497
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3. Research on convolutional neural networks in motor fault diagnosis;Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023);2024-04-01
4. A lightweight fault diagnosis model for planetary gearbox using domain adaptation and model compression;Journal of Vibroengineering;2024-01-23
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