Intelligent Machinery Fault Diagnosis With Event-Based Camera
Author:
Affiliation:
1. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi'an Jiaotong University, Xi'an, Shaanxi, China
Funder
National Science Fund for Distinguished Young Scholars of China
Fundamental Research Funds for the Central Universities
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/ielx7/9424/10355676/10086648.pdf?arnumber=10086648
Reference35 articles.
1. Task-Sequencing Meta Learning for Intelligent Few-Shot Fault Diagnosis with Limited Data
2. Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning
3. A Robust Deep Learning Network for Low-speed Machinery Fault Diagnosis based on Multi-kernel and RPCA
4. Imbalanced fault diagnosis of rolling bearing using improved MsR-GAN and feature enhancement-driven CapsNet
5. Knowledge mapping-based adversarial domain adaptation: A novel fault diagnosis method with high generalizability under variable working conditions
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