Digital twin-assisted AI framework based on domain adaptation for bearing defect diagnosis in the centrifugal pump-Reference-Cited by-同舟云学术

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Digital twin-assisted AI framework based on domain adaptation for bearing defect diagnosis in the centrifugal pump

Published:2024-08 Issue: Volume:235 Page:115013
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Kumar Anil^ORCID,Kumar Rajesh,Xiang Jiawei,Qiao Zijian,Zhou Youqing,Shao Haidong

Publisher

Elsevier BV

Reference30 articles.

1. Research on fault diagnosis technology of centrifugal pump blade crack based on PCA and GMM;Cao;Measurement,2021

2. Adaptive variational autoencoding generative adversarial networks for rolling bearing fault diagnosis;Wang;Adv. Eng. Inf.,2023

3. Conditional distribution-guided adversarial transfer learning network with multi-source domains for rolling bearing fault diagnosis;Wu;Adv. Eng. Inf.,2023

4. Machine fault diagnosis with small sample based on variational information constrained generative adversarial network;Liu;Adv. Eng. Inf.,2022

5. A novel adaptive convolutional neural network for fault diagnosis of hydraulic piston pump with acoustic images;Tang;Adv. Eng. Inf.,2022

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Federated Adversarial Fault Diagnosis Method Driven by Fault Information Discrepancy;Entropy;2024-08-23

2. Editorial: Application of digital twin technology in prognostic and health management of complex machineries;Measurement;2024-08

3. Damage identification for mining wire rope based on continuous wavelet transform and convolutional neural network;Nondestructive Testing and Evaluation;2024-07-24

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