Deep Joint Distribution Alignment: A Novel Enhanced-Domain Adaptation Mechanism for Fault Transfer Diagnosis-Reference-Cited by-同舟云学术

Deep Joint Distribution Alignment: A Novel Enhanced-Domain Adaptation Mechanism for Fault Transfer Diagnosis

Published:2023-05 Issue:5 Volume:53 Page:3128-3138
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Qin Yi¹^ORCID,Qian Quan¹^ORCID,Luo Jun¹^ORCID,Pu Huayan¹^ORCID

Affiliation:

1. State Key Laboratory of Mechanical Transmission, College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China

Funder

National Natural Science Foundation of China

Graduate Research and Innovation Foundation of Chongqing, China

Chongqing Research Program of Basic Research and Frontier Exploration

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221036/10106628/09756646.pdf?arnumber=9756646

Reference34 articles.

1. Multiscale Transfer Voting Mechanism: A New Strategy for Domain Adaption

2. A new deep transfer learning network based on convolutional auto-encoder for mechanical fault diagnosis

3. Deep domain confusion: Maximizing for domain invariance;tzeng;arXiv 1412 3474,2014

4. Deep CORAL: Correlation Alignment for Deep Domain Adaptation

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