Adversarial Domain Adaptation Approach for Axial Piston Pump Fault Diagnosis Under Small Sample Condition Based on Measured and Simulated Signals-Reference-Cited by-同舟云学术

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Adversarial Domain Adaptation Approach for Axial Piston Pump Fault Diagnosis Under Small Sample Condition Based on Measured and Simulated Signals

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhang Yefeng¹^ORCID,He You¹^ORCID,Tang Hesheng¹^ORCID,Ren Yan¹^ORCID,Xiang Jiawei¹^ORCID

Affiliation:

1. College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, China

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Wenzhou Major Science and Technology Innovation Project of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10494338.pdf?arnumber=10494338

Reference35 articles.

1. Novel virtual sample generation using conditional GAN for developing soft sensor with small data

2. Machinery Fault Diagnosis Based on Domain Adaptation to Bridge the Gap Between Simulation and Measured Signals

3. Potential, challenges and future directions for deep learning in prognostics and health management applications

4. Modified adaptive discrete-time incremental nonlinear dynamic inversion control for quad-rotors in the presence of motor faults

5. A data indicator-based deep belief networks to detect multiple faults in axial piston pumps

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