An Intelligent Method for Early Motor Bearing Fault Diagnosis Based on Wasserstein Distance Generative Adversarial Networks Meta Learning-Reference-Cited by-同舟云学术

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An Intelligent Method for Early Motor Bearing Fault Diagnosis Based on Wasserstein Distance Generative Adversarial Networks Meta Learning

Published:2023 Issue: Volume:72 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Luo Peien¹^ORCID,Yin Zhonggang¹^ORCID,Yuan Dongsheng¹^ORCID,Gao Fengtao¹^ORCID,Liu Jing²^ORCID

Affiliation:

1. Department of Electrical Engineering, Xi’an University of Technology, Xi’an, China

2. Department of Electronic Engineering, Xi’an University of Technology, Xi’an, China

Funder

National Natural Science Foundation of China

Nature Science Basic Research Plan in Shaanxi Province

Key Research and Development Project of Shaanxi Province

China Postdoctoral Science Foundation

Science and Technology Innovation Team in Shaanxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10130390.pdf?arnumber=10130390

Reference37 articles.

1. Diagnostic of Combined Mechanical and electrical faults in ASD-powered Induction Motor using MODWT and a Lightweight 1D CNN

2. Intelligent Fault Diagnosis of Rotary Machines: Conditional Auxiliary Classifier GAN Coupled With Meta Learning Using Limited Data

3. Early Bearing Fault Diagnosis of Rotating Machinery by 1D Self-Organized Operational Neural Networks

4. Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning

5. Fault Diagnosis of Bearings Based on Multi-Sensor Information Fusion and 2D Convolutional Neural Network

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2. An Unsupervised Framework Based on Dual-Domain Contrastive Learning and Tri-Indicator Joint Alarm Strategy for Early Fault Detection of Bearing;IEEE Sensors Journal;2024-08-15

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4. Dual-weight attention-based multi-source multi-stage alignment domain adaptation for industrial fault diagnosis;Measurement Science and Technology;2024-06-05

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