An Unsupervised Domain Adaption Method for Fault Diagnosis via Multichannel Variational Hypergraph Autoencoder-Reference-Cited by-同舟云学术

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An Unsupervised Domain Adaption Method for Fault Diagnosis via Multichannel Variational Hypergraph Autoencoder

Published:2024 Issue: Volume:73 Page:1-16
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Luo Xiangmin¹^ORCID,Chen Ziwei¹^ORCID,Huang Da²^ORCID,Lei Fangyuan³^ORCID,Wang Chang-Dong³^ORCID,Yi Liao Iman⁴^ORCID

Affiliation:

1. School of Electronic and Information Engineering, Guangdong Polytechnic Normal University, Guangzhou, China

2. Faculty of Applied Sciences, Macao Polytechnic University, Macao, China

3. Guangdong Provincial Key Laboratory of Intellectual Property and Big Data, Guangdong Polytechnic Normal University, Guangzhou, China

4. School of Computer Science, University of Nottingham Malaysia, Semenyih, Malaysia

Funder

Guangdong Provincial Key Laboratory of Intellectual Property and Big Data

National Natural Science Foundation of China

Special Projects for Key Fields in Higher Education of Guangdong

Key Discipline Research Capacity Improvement Project of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10535302.pdf?arnumber=10535302

Reference54 articles.

1. Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives

2. Application of sensor data based predictive maintenance and artificial neural networks to enable Industry 4.0

3. A novel energy evaluation approach of machining processes based on data analysis

4. Intelligent Detection Method of Forgings Defects Detection Based on Improved EfficientNet and Memetic Algorithm

5. Triplet adversarial Learning-driven graph architecture search network augmented with Probsparse-attention mechanism for fault diagnosis under Few-shot & Domain-shift

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